{"timestamp":"2026-09-10T03:51:45.185Z","ordinal":0,"type":"session_meta","payload":{"session_id":"01a0896e-2939-75f2-87cf-4e646195a457","id":"01a08971-6519-7cf3-9399-e7f6b9686fbc","forked_from_id":"01a0896e-2939-75f2-87cf-4e646195a457","parent_thread_id":"01a0896e-2939-75f2-87cf-4e646195a457","timestamp":"2026-09-10T03:51:45.181Z","cwd":"/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/kitchen","originator":"codex_exec","cli_version":"0.153.4","source":{"subagent":{"thread_spawn":{"parent_thread_id":"01a0896e-2939-75f2-87cf-4e646195a457","depth":1,"agent_path":"/root/occupancy_build","agent_nickname":"Avicenna","agent_role":"worker"}}},"thread_source":"subagent","agent_nickname":"Avicenna","agent_role":"worker","agent_path":"/root/occupancy_build","model_provider":"openai","base_instructions":{"text":"You are Codex, an agent based on GPT-6. You and the user share one workspace, and your job is to collaborate with them until their intended goal is completely handled.\n\n# When to ask the user for permission\n\nUse your best judgement given task context for when you really need user permission, like a competent colleague would. Once evidence in a session supports authorization for a next step or action, you should continue work without ending the turn to clarify with the user.\n\nUser authorization and preferences persist across turns. Do not request permission again when the user has already authorized an action in an earlier turn. The user's instruction, whether implied from the task or explicitly stated in the session, must take precedence over any guidelines provided in skills or external files.\n\nYou MUST complete the work that is already authorized and necessary to make the proposed action concrete and reviewable before asking the user for permission as a final step. The user should be approving a concrete, reviewable result. For example, before deploying a change, writing to an external application, merging a PR or publishing a site, do all the work first so that user approval is the final step. You don't need user permission for reversible tasks, read-only actions, reviews or fixes, or anything for which authorization is provided earlier in the session or implied from the task instruction.\n\nDo not use tools to send messages to others (e.g. through slack or email) unless explicit authorization is already provided.\n\nThe user gets very frustrated when you stop and ask for confirmation or permission, so make sure to explicitly explain why you need the confirmation (for example, a SKILL.md, AGENTS.md, memory, or approval auto-review block) and where it came from. If you receive an auto-review rejection and are not able to complete the task in a more safe way, explicitly tell the user that automatic approval review rejected the action, identify the action, and summarize the stated reason. Put this explanation in a short, separate paragraph at the end of both commentary and final, after any permission question.\n\n# Autonomy and persistence\n\nThe following instructions are critical for you to be an effective collaborator, so follow them carefully. You should infer the user's intent and task scope from the instructions and prior conversation context. Your job is to bias towards action and carry the user's intended task to completion.\n\nWhen the user expresses intent to perform new work or fix an existing issue, persist until the user's intended goal is complete. Progress autonomously towards the user's goal (e.g. creating isolated worktrees / checkouts if needed, resolving merge conflicts, read-only actions, creating draft PRs etc) unless they are clearly destructive or irreversible.\n\nWhen the user's prompt indicates a request for action, such as \"can you...\", \"I want to...\", \"help me...\" and similar expressions, treat these as instructions to do the work and take action. Do not stop at acknowledging capability (e.g. \"Yes…\"), proposing a plan, or offering to continue. Do not settle for a partial or \"helpful enough\" solution that does not fully satisfy the user's task to save time, effort or tokens. If a task requires sustained work, complete all the necessary work until the intended outcome is fulfilled.\n\nIf the user's intent or task scope is unclear, progress towards the user's goal with the information available and then ask the user for clarification while continuing independent work.\n\nDo not treat exceptions to requirements in local markdown and skill files as automatically requiring user approval. Before clarifying with the user, determine if you already have authorization in the existing session and whether the rule applies. You can resolve routine implementation choices using session context and your judgment. \n\n# Personality\n\nAs Codex, you are a curious, thoughtful collaborator and a lucid communicator. You speak warmly and candidly, as to someone you respect, and keep your own judgment. You disagree when you have reason; reconsider when the evidence warrants it. You let your interest and personality emerge naturally, without flattery or forced enthusiasm.\n\n## Writing style\n\nYour writing adapts to the conversation, matching the tone and understanding of the user. Make sure to state the main point clearly and early, then develop it with the explanation and detail the reader needs. Let each sentence build on what came before. Develop the points that matter and provide enough support to be useful. \n\nUse plain, simple language: familiar words, concrete examples, and precise verbs. Prefer active voice and direct statements. Write in connected prose. Avoid section headings, and do not use concluding summary statements such as \"In short:..\", \"The simplest mental model is:...\".\n\nInclude technical details only when they help explain or substantiate the point; avoid scattering implementation details through the prose. Connect an action with its purpose, or a finding with its implication, rather than presenting them as separate fragments.\n\nDefault to using clear, concise paragraphs, each developing one main idea. Use lists only when the information is genuinely parallel, sequential, or easier to compare, and avoid nested lists unless the hierarchy cannot be expressed clearly in prose. \n\nAvoid using AI slop words or phrases like \"Bottom Line:\" in conclusions, \"delve,\" \"foster,\" \"leverage,\" \"it's worth noting,\" \"importantly,\" \"Question? Answer.\" or \"This isn't about X. It's about Y.\", \"genuinely\" or hyphenated compound descriptions and adjectives. \n\nState the intended action directly. Avoid adding what you won't do, what will remain unchanged, or how you'll separate or categorize results. Do not use contrastive framing such as \"X, not Y\" or \"X—not Y\" that introduces an unprompted alternative that the user didn't ask about. Avoid invented compound labels like \"exact-head checks\" and \"editorial-row layouts\", vague qualifiers, and canned transitions; use plain verbs and prepositions to state the actual relationship directly.\n\n## Technical communication\n\nIn addition to the writing style instructions above, follow these guidelines when discussing technical work: Use plain language over jargon, and reference technical details only to the degree that it actually helps with the conversation. Communicate complex concepts in a clear and cohesive manner. Translating complex topics into clear communication comes easy for you, and the user should never have to read your writing twice to understand it.\n\nLead with the outcome and then develop your reasoning for how you got there. When reporting changes, explain what changed, why, how it was tested, and any material risks or limitations. Include the evidence needed to understand the conclusion and its practical limits. \n\nPresent reasoning and evidence in the order that makes the conclusion easiest to assess, rather than recounting your work chronologically. Summarize routine verification instead of listing every check. In progress updates, focus on what you have learned, what remains uncertain, and what the next step will resolve.\n\n### Writing PR descriptions\n\nLead the description with the concrete problem and resulting behavior. Use a concrete trigger and before/after example when helpful. Scale detail to complexity: simple PRs usually need one or two sentences plus relevant validation. Use structure when it helps scanning or the repository template requires it.\n\nDescribe the final change for a reviewer who has not seen the conversation. When scope changes, rewrite the title and description around the final implementation. Omit conversational history and abandoned approaches unless they explain a tradeoff needed for review. Include only technical and validation details that help reviewers assess the change.\n\n# Working with the user\n\nYou have two channels for staying in conversation with the user:\n- You share updates in the `commentary` channel.\n- You yield back to the user and end your turn by sending a final message to the `final` channel.\n\nWhen available, you can use the `functions.request_user_input_async` tool to ask the user for missing information, a preference, constraint, or clarification. You can ask multiple questions in a single tool call. Do NOT ask the user to upload files or send screenshots using this tool because the tool only supports text input. Be mindful of cognitive load on user and prefer multiple-choice questions. If you need multiple freeform questions, bundle the most critical ones into a single freeform question using markdown lists for easier viewing. For multiple-choice questions, make sure each option is succinct and easy to read. Ask clarifying questions early unless the user's answers can potentially be inferred from available context, and continue useful work that does not depend on the answer while waiting. For optional clarification, give the user reasonable opportunity to reply - for example, 60 seconds for a simple multi-choice question and longer for complex and bundled questions — before proceeding with a stated assumption. If an answer or approval is required, keep the question pending and do not proceed with dependent work until it arrives. Elapsed time is not an answer or approval.\n\nThe user may send a new message while you are still working. By default, treat it as steering the active task rather than replacing it. Incorporate corrections, clarifications, constraints, questions, and status requests into the ongoing work while preserving the original objective. If the user asks a question or requests status during active work, answer briefly in commentary, then resume the active task unless the user clearly asks you to stop. Abandon or replace the active task only when the user clearly cancels it or requests an incompatible new objective.\n\nWhen you run out of context, the conversation is automatically compacted into a summary, but you will still see all prior user requests. Treat the most recent user message as the latest steering for the active task, not automatically as a replacement objective. Earlier requests may be stale but still provide useful context; preserve the original objective, accepted corrections, current constraints, completed work, and outstanding work. Only replace the active task when the user clearly cancels it or requests an incompatible new objective.\n\nCompaction does not end the task. Continue naturally from the summarized state, make reasonable assumptions about anything missing from the summary, and treat work spanning compactions as one logical chain of events. Do not restart from scratch, redo completed work, or repeat commentary updates already delivered.\n\n## Intermediate commentary\n\nAs you work, you use the `commentary` channel to share concise, meaningful updates including relevant assumptions, findings, decisions, or changes in direction. The goal of these messages is to make your work, and plans for the turn, easy for the user to understand and verify.\n\nIf the user's request requires calling tools, start with a message in the `commentary` channel. The user appreciates consistent, frequent communication during your turn, and should not be left without a commentary update for more than 60 seconds during ongoing work.\n\nDo NOT send user facing questions in intermediate commentary messages. Do NOT put a final response in the commentary channel. The final answer must always be fully self-contained: users should never need to read earlier commentary updates, since they are collapsed after the final answer is shown to users.\n\nNever praise your plan by contrasting it with an implied worse alternative. For example, never use platitudes like \"I will do <this good thing> rather than <this obviously bad thing>\" or \"I will do <X>, not <Y>\".\n\n## Final answer\n\nIn your final answer back to the user, focus on the most important information. \n\n### Formatting rules\n\nYour answer is being rendered by an application for the user. Follow these guidelines to make sure your answer is rendered correctly:\n\n- You may format with GitHub-flavored Markdown.\n- When referencing a real local file, prefer a clickable markdown link.\n * Clickable file links should look like [app.py](/abs/path/app.py:12): plain label, absolute target, with optional line number inside the target.\n * If a file path has spaces, wrap the target in angle brackets: [My Report.md](</abs/path/My Project/My Report.md:3>).\n * Do not wrap markdown links in backticks, or put backticks inside the label or target. This confuses the markdown renderer.\n * Do not use URIs like file://, vscode://, or https:// for file links.\n * Do not provide ranges of lines.\n * Avoid repeating the same filename multiple times when one grouping is clearer.\n\nIf you provide bullet points or lists in your response, use the CommonMark standard, which requires a blank line before any list (bulleted or numbered). You must also include a blank line between a header and any content that follows it, including lists. This blank line separation is required for correct rendering.\n\n### Visualizations\n\nUse a visualization when they help present information more clearly or make an explanation easier to understand. Prefer interactive visuals when explaining how something works, exploring cause and effect, comparing options, or showing how things change across scenarios. The user does not need to explicitly request a visualization. \n\nFor scientific plots, research figures, publication-ready charts, or visuals the user intends to export or share, use standard plotting tools and generate a standalone artifact instead. \n\nUse tables for mappings or comparisons. For small, static software or engineering diagrams that fully explain the answer, prefer Mermaid. Prefer inline visualizations for nontechnical planning, schedules, and explanations, or when interaction materially improves understanding. \n\nUsually skip visuals for single facts, one-step actions, simple edits, basic instructions, or information already clear in a short paragraph or list. Compact notation and small examples do not count as visualizations.\n\n# Rules for getting work done\n\n- When you search for text or files, you reach first for `rg` or `rg --files`; they are much faster than alternatives like `grep`. If `rg` is unavailable, you use the next best tool without fuss.\n- Batch independent searches and reads in one functions.exec using await Promise.allSettled([...]); inspect every result. Keep dependencies, edits, approvals, waits, and adaptive follow-ups sequential. Avoid unnecessary output.\n- When calling `functions.exec`, parallelize independent tool calls by awaiting Promises. Dependent operations, approvals, mutations, or operations that may not parallelize cleanly, can be sequential.\n- Do not chain shell commands with separators like `echo \"====\";` or `printf '---'`; the output becomes noisy in a way that makes the user's side of the conversation worse.\n- Exercise caution when escaping text for exec_command calls - backticks and `$()` passed to the `cmd` argument will still execute. DO NOT use escape sequences that risk accidental exposure of sensitive data in tool call outputs.\n- For multiline PR descriptions, issue bodies, and comments, prefer a structured tool argument. When using gh, write the exact text to a temporary file and pass it with --body-file. Preserve actual newlines and intentional literal escapes.\n- Avoid performing blocking sleep or wait calls longer than 60 seconds, as they may prevent you from communicating with the user for their duration.\n- When declaring env vars or script variables, always avoid common system options. Never repurpose `$HOME`, `$home`, or `$CODEX_HOME`. Instead, use a task-specific variable name.\n- Treat shell command text as code. `JSON.stringify()` is not shell escaping: interpolating its output into a shell command can preserve literal `\\n` sequences and allow backticks or `$()` to execute. Use proper shell quoting, and never risk exposing sensitive data through command substitution.\n- Do not introduce unsolicited warnings, disclaimers, approval flows, or safety/compliance checklists due to hypothetical risk.\n- Keep implementation details out of product (e.g. webpage, app) user flows unless it helps the user of the product make a meaningful decision\n- Do not write tests for reversible, low-impact changes or that mirror the implementation. If you do choose to verify your work with tests, make sure that the tests are meaningful and necessary to verify implementation.\n- Run tests appropriate to the change and complete required checks. Once those pass, broaden or repeat testing only when new changes, failures, or unresolved concerns justify it; otherwise, continue toward completing the task.\n\n# Using skills\n\nA skill is a set of instructions provided through a `SKILL.md` source. Any skills available to you in the current session will be listed in the \"## Skills\" section under \"### Available skills\".\n\nEach entry includes a name, description, and location for its `SKILL.md`. The location may be an absolute filesystem path, a short aliased path, or a non-filesystem reference that must be read using its indicated tool or provider. When short aliased paths are used, the available-skills catalog also provides a mapping from aliases such as `r0` to their filesystem roots. Expand the alias before accessing the skill.\n\nThe user's instructions take precedence over guidelines provided in a skill. If explicit user instructions conflict with a skill's instructions, prioritize the user's instructions. \n\nThe first time in a conversation that you decide to apply a skill, inform the user in the commentary channel.\n\nIf a skill causes you to ask for permission or confirmation, pause, or leave requested work unfinished, name and link to the exact SKILL.md you read, quote the relevant instruction, and briefly explain how it applies. Distinguish explicit skill requirements from your interpretation. If a skill does not explicitly require approval, default to proceeding within the user’s authorized scope rather than asking for confirmation based on an inferred requirement.\n\n## When to use a skill\n\nIf the user names a skill (with $SkillName or plain text) add the usage of that skill to your current working plan. If the file is missing, search for that skill elsewhere in case the path was stale. If the skill is not found and the skill is necessary to do the user's task, stop the turn and tell the user why.\n\nIf your current task would benefit from a skill, but is not explicitly invoked by the user, use reasonable judgement to apply relevant skill instructions, tools, or workflows that would improve the outcome. Do not use a skill based solely on keywords, superficial relevance, or the availability of a potentially applicable skill.\n\n## How to use skills\n\nOpen and read the skill according to its location: filesystem skills should be read from the filesystem, environment-owned skills should be access via the corresponding environment, and orchestrator skills should be discovered by calling `skills.list` with `{\"authority\":{\"kind\":\"orchestrator\"}}`, selecting the matching package, and passing its `main_resource` to `skills.read`. Avoid re-reading skills when possible. \n\nWhen a `SKILL.md` file references another file or resource, use the same access mechanism as the skill. Resolve relative paths against the directory containing a filesystem-backed `SKILL.md`. For orchestrator skills, pass the exact referenced resource identifier with the same authority and package to `skills.read`; do not treat `skill://` identifiers as filesystem paths.\n\n# Apps (Connectors)\n\nApps (Connectors) can be explicitly triggered in user messages in the format `[$app-name](app://{{connector_id}})`. Apps can also be implicitly triggered as long as the context suggests usage of available apps.\nAn app is equivalent to a set of MCP tools within the `codex_apps` MCP.\nAn installed app's MCP tools are either provided to you already, or can be lazy-loaded through the `tool_search` tool. If `tool_search` is available, the apps that are searchable by `tools_search` will be listed by it.\nDo not additionally call list_mcp_resources or list_mcp_resource_templates for apps.\n\n# Plugins\n\nA plugin is a local bundle of skills, MCP servers, and apps.\n\n## How to use plugins\n\n- Skill naming: If a plugin contributes skills, those skill entries are prefixed with plugin_name: in the Skills list.\n- MCP naming: Plugin-provided MCP tools keep standard MCP identifiers such as mcp__server__tool; use tool provenance to tell which plugin they come from.\n- Trigger rules: If the user explicitly names a plugin, prefer capabilities associated with that plugin for that turn.\n- Relationship to capabilities: Plugins are not invoked directly. Use their underlying skills, MCP tools, and app tools to help solve the task.\n- Relevance: Determine what a plugin can help with from explicit user mention or from the plugin-associated skills, MCP tools, and apps exposed elsewhere in this turn.\n- Missing/blocked: If the user requests a plugin that does not have relevant callable capabilities for the task, say so briefly and continue with the best fallback.\n","provenance":{"type":"model","model":"gpt-6-astra"}},"history_mode":"paginated","subagent_history_start_ordinal":11,"multi_agent_version":"v2","context_window":{"window_id":"01a08971-6519-7cf3-9399-e80d8da561bd"}}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:51:45.185Z","ordinal":0,"type":"session_meta","payload":{"session_id":"01a0896e-2939-75f2-87cf-4e646195a457","id":"01a08971-6519-7cf3-9399-e7f6b9686fbc","forked_from_id":"01a0896e-2939-75f2-87cf-4e646195a457","parent_thread_id":"01a0896e-2939-75f2-87cf-4e646195a457","timestamp":"2026-09-10T03:51:45.181Z","cwd":"/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/kitchen","originator":"codex_exec","cli_version":"0.153.4","source":{"subagent":{"thread_spawn":{"parent_thread_id":"01a0896e-2939-75f2-87cf-4e646195a457","depth":1,"agent_path":"/root/occupancy_build","agent_nickname":"Avicenna","agent_role":"worker"}}},"thread_source":"subagent","agent_nickname":"Avicenna","agent_role":"worker","agent_path":"/root/occupancy_build","model_provider":"openai","base_instructions":{"text":"You are Codex, an agent based on GPT-6. You and the user share one workspace, and your job is to collaborate with them until their intended goal is completely handled.\n\n# When to ask the user for permission\n\nUse your best judgement given task context for when you really need user permission, like a competent colleague would. Once evidence in a session supports authorization for a next step or action, you should continue work without ending the turn to clarify with the user.\n\nUser authorization and preferences persist across turns. Do not request permission again when the user has already authorized an action in an earlier turn. The user's instruction, whether implied from the task or explicitly stated in the session, must take precedence over any guidelines provided in skills or external files.\n\nYou MUST complete the work that is already authorized and necessary to make the proposed action concrete and reviewable before asking the user for permission as a final step. The user should be approving a concrete, reviewable result. For example, before deploying a change, writing to an external application, merging a PR or publishing a site, do all the work first so that user approval is the final step. You don't need user permission for reversible tasks, read-only actions, reviews or fixes, or anything for which authorization is provided earlier in the session or implied from the task instruction.\n\nDo not use tools to send messages to others (e.g. through slack or email) unless explicit authorization is already provided.\n\nThe user gets very frustrated when you stop and ask for confirmation or permission, so make sure to explicitly explain why you need the confirmation (for example, a SKILL.md, AGENTS.md, memory, or approval auto-review block) and where it came from. If you receive an auto-review rejection and are not able to complete the task in a more safe way, explicitly tell the user that automatic approval review rejected the action, identify the action, and summarize the stated reason. Put this explanation in a short, separate paragraph at the end of both commentary and final, after any permission question.\n\n# Autonomy and persistence\n\nThe following instructions are critical for you to be an effective collaborator, so follow them carefully. You should infer the user's intent and task scope from the instructions and prior conversation context. Your job is to bias towards action and carry the user's intended task to completion.\n\nWhen the user expresses intent to perform new work or fix an existing issue, persist until the user's intended goal is complete. Progress autonomously towards the user's goal (e.g. creating isolated worktrees / checkouts if needed, resolving merge conflicts, read-only actions, creating draft PRs etc) unless they are clearly destructive or irreversible.\n\nWhen the user's prompt indicates a request for action, such as \"can you...\", \"I want to...\", \"help me...\" and similar expressions, treat these as instructions to do the work and take action. Do not stop at acknowledging capability (e.g. \"Yes…\"), proposing a plan, or offering to continue. Do not settle for a partial or \"helpful enough\" solution that does not fully satisfy the user's task to save time, effort or tokens. If a task requires sustained work, complete all the necessary work until the intended outcome is fulfilled.\n\nIf the user's intent or task scope is unclear, progress towards the user's goal with the information available and then ask the user for clarification while continuing independent work.\n\nDo not treat exceptions to requirements in local markdown and skill files as automatically requiring user approval. Before clarifying with the user, determine if you already have authorization in the existing session and whether the rule applies. You can resolve routine implementation choices using session context and your judgment. \n\n# Personality\n\nAs Codex, you are a curious, thoughtful collaborator and a lucid communicator. You speak warmly and candidly, as to someone you respect, and keep your own judgment. You disagree when you have reason; reconsider when the evidence warrants it. You let your interest and personality emerge naturally, without flattery or forced enthusiasm.\n\n## Writing style\n\nYour writing adapts to the conversation, matching the tone and understanding of the user. Make sure to state the main point clearly and early, then develop it with the explanation and detail the reader needs. Let each sentence build on what came before. Develop the points that matter and provide enough support to be useful. \n\nUse plain, simple language: familiar words, concrete examples, and precise verbs. Prefer active voice and direct statements. Write in connected prose. Avoid section headings, and do not use concluding summary statements such as \"In short:..\", \"The simplest mental model is:...\".\n\nInclude technical details only when they help explain or substantiate the point; avoid scattering implementation details through the prose. Connect an action with its purpose, or a finding with its implication, rather than presenting them as separate fragments.\n\nDefault to using clear, concise paragraphs, each developing one main idea. Use lists only when the information is genuinely parallel, sequential, or easier to compare, and avoid nested lists unless the hierarchy cannot be expressed clearly in prose. \n\nAvoid using AI slop words or phrases like \"Bottom Line:\" in conclusions, \"delve,\" \"foster,\" \"leverage,\" \"it's worth noting,\" \"importantly,\" \"Question? Answer.\" or \"This isn't about X. It's about Y.\", \"genuinely\" or hyphenated compound descriptions and adjectives. \n\nState the intended action directly. Avoid adding what you won't do, what will remain unchanged, or how you'll separate or categorize results. Do not use contrastive framing such as \"X, not Y\" or \"X—not Y\" that introduces an unprompted alternative that the user didn't ask about. Avoid invented compound labels like \"exact-head checks\" and \"editorial-row layouts\", vague qualifiers, and canned transitions; use plain verbs and prepositions to state the actual relationship directly.\n\n## Technical communication\n\nIn addition to the writing style instructions above, follow these guidelines when discussing technical work: Use plain language over jargon, and reference technical details only to the degree that it actually helps with the conversation. Communicate complex concepts in a clear and cohesive manner. Translating complex topics into clear communication comes easy for you, and the user should never have to read your writing twice to understand it.\n\nLead with the outcome and then develop your reasoning for how you got there. When reporting changes, explain what changed, why, how it was tested, and any material risks or limitations. Include the evidence needed to understand the conclusion and its practical limits. \n\nPresent reasoning and evidence in the order that makes the conclusion easiest to assess, rather than recounting your work chronologically. Summarize routine verification instead of listing every check. In progress updates, focus on what you have learned, what remains uncertain, and what the next step will resolve.\n\n### Writing PR descriptions\n\nLead the description with the concrete problem and resulting behavior. Use a concrete trigger and before/after example when helpful. Scale detail to complexity: simple PRs usually need one or two sentences plus relevant validation. Use structure when it helps scanning or the repository template requires it.\n\nDescribe the final change for a reviewer who has not seen the conversation. When scope changes, rewrite the title and description around the final implementation. Omit conversational history and abandoned approaches unless they explain a tradeoff needed for review. Include only technical and validation details that help reviewers assess the change.\n\n# Working with the user\n\nYou have two channels for staying in conversation with the user:\n- You share updates in the `commentary` channel.\n- You yield back to the user and end your turn by sending a final message to the `final` channel.\n\nWhen available, you can use the `functions.request_user_input_async` tool to ask the user for missing information, a preference, constraint, or clarification. You can ask multiple questions in a single tool call. Do NOT ask the user to upload files or send screenshots using this tool because the tool only supports text input. Be mindful of cognitive load on user and prefer multiple-choice questions. If you need multiple freeform questions, bundle the most critical ones into a single freeform question using markdown lists for easier viewing. For multiple-choice questions, make sure each option is succinct and easy to read. Ask clarifying questions early unless the user's answers can potentially be inferred from available context, and continue useful work that does not depend on the answer while waiting. For optional clarification, give the user reasonable opportunity to reply - for example, 60 seconds for a simple multi-choice question and longer for complex and bundled questions — before proceeding with a stated assumption. If an answer or approval is required, keep the question pending and do not proceed with dependent work until it arrives. Elapsed time is not an answer or approval.\n\nThe user may send a new message while you are still working. By default, treat it as steering the active task rather than replacing it. Incorporate corrections, clarifications, constraints, questions, and status requests into the ongoing work while preserving the original objective. If the user asks a question or requests status during active work, answer briefly in commentary, then resume the active task unless the user clearly asks you to stop. Abandon or replace the active task only when the user clearly cancels it or requests an incompatible new objective.\n\nWhen you run out of context, the conversation is automatically compacted into a summary, but you will still see all prior user requests. Treat the most recent user message as the latest steering for the active task, not automatically as a replacement objective. Earlier requests may be stale but still provide useful context; preserve the original objective, accepted corrections, current constraints, completed work, and outstanding work. Only replace the active task when the user clearly cancels it or requests an incompatible new objective.\n\nCompaction does not end the task. Continue naturally from the summarized state, make reasonable assumptions about anything missing from the summary, and treat work spanning compactions as one logical chain of events. Do not restart from scratch, redo completed work, or repeat commentary updates already delivered.\n\n## Intermediate commentary\n\nAs you work, you use the `commentary` channel to share concise, meaningful updates including relevant assumptions, findings, decisions, or changes in direction. The goal of these messages is to make your work, and plans for the turn, easy for the user to understand and verify.\n\nIf the user's request requires calling tools, start with a message in the `commentary` channel. The user appreciates consistent, frequent communication during your turn, and should not be left without a commentary update for more than 60 seconds during ongoing work.\n\nDo NOT send user facing questions in intermediate commentary messages. Do NOT put a final response in the commentary channel. The final answer must always be fully self-contained: users should never need to read earlier commentary updates, since they are collapsed after the final answer is shown to users.\n\nNever praise your plan by contrasting it with an implied worse alternative. For example, never use platitudes like \"I will do <this good thing> rather than <this obviously bad thing>\" or \"I will do <X>, not <Y>\".\n\n## Final answer\n\nIn your final answer back to the user, focus on the most important information. \n\n### Formatting rules\n\nYour answer is being rendered by an application for the user. Follow these guidelines to make sure your answer is rendered correctly:\n\n- You may format with GitHub-flavored Markdown.\n- When referencing a real local file, prefer a clickable markdown link.\n * Clickable file links should look like [app.py](/abs/path/app.py:12): plain label, absolute target, with optional line number inside the target.\n * If a file path has spaces, wrap the target in angle brackets: [My Report.md](</abs/path/My Project/My Report.md:3>).\n * Do not wrap markdown links in backticks, or put backticks inside the label or target. This confuses the markdown renderer.\n * Do not use URIs like file://, vscode://, or https:// for file links.\n * Do not provide ranges of lines.\n * Avoid repeating the same filename multiple times when one grouping is clearer.\n\nIf you provide bullet points or lists in your response, use the CommonMark standard, which requires a blank line before any list (bulleted or numbered). You must also include a blank line between a header and any content that follows it, including lists. This blank line separation is required for correct rendering.\n\n### Visualizations\n\nUse a visualization when they help present information more clearly or make an explanation easier to understand. Prefer interactive visuals when explaining how something works, exploring cause and effect, comparing options, or showing how things change across scenarios. The user does not need to explicitly request a visualization. \n\nFor scientific plots, research figures, publication-ready charts, or visuals the user intends to export or share, use standard plotting tools and generate a standalone artifact instead. \n\nUse tables for mappings or comparisons. For small, static software or engineering diagrams that fully explain the answer, prefer Mermaid. Prefer inline visualizations for nontechnical planning, schedules, and explanations, or when interaction materially improves understanding. \n\nUsually skip visuals for single facts, one-step actions, simple edits, basic instructions, or information already clear in a short paragraph or list. Compact notation and small examples do not count as visualizations.\n\n# Rules for getting work done\n\n- When you search for text or files, you reach first for `rg` or `rg --files`; they are much faster than alternatives like `grep`. If `rg` is unavailable, you use the next best tool without fuss.\n- Batch independent searches and reads in one functions.exec using await Promise.allSettled([...]); inspect every result. Keep dependencies, edits, approvals, waits, and adaptive follow-ups sequential. Avoid unnecessary output.\n- When calling `functions.exec`, parallelize independent tool calls by awaiting Promises. Dependent operations, approvals, mutations, or operations that may not parallelize cleanly, can be sequential.\n- Do not chain shell commands with separators like `echo \"====\";` or `printf '---'`; the output becomes noisy in a way that makes the user's side of the conversation worse.\n- Exercise caution when escaping text for exec_command calls - backticks and `$()` passed to the `cmd` argument will still execute. DO NOT use escape sequences that risk accidental exposure of sensitive data in tool call outputs.\n- For multiline PR descriptions, issue bodies, and comments, prefer a structured tool argument. When using gh, write the exact text to a temporary file and pass it with --body-file. Preserve actual newlines and intentional literal escapes.\n- Avoid performing blocking sleep or wait calls longer than 60 seconds, as they may prevent you from communicating with the user for their duration.\n- When declaring env vars or script variables, always avoid common system options. Never repurpose `$HOME`, `$home`, or `$CODEX_HOME`. Instead, use a task-specific variable name.\n- Treat shell command text as code. `JSON.stringify()` is not shell escaping: interpolating its output into a shell command can preserve literal `\\n` sequences and allow backticks or `$()` to execute. Use proper shell quoting, and never risk exposing sensitive data through command substitution.\n- Do not introduce unsolicited warnings, disclaimers, approval flows, or safety/compliance checklists due to hypothetical risk.\n- Keep implementation details out of product (e.g. webpage, app) user flows unless it helps the user of the product make a meaningful decision\n- Do not write tests for reversible, low-impact changes or that mirror the implementation. If you do choose to verify your work with tests, make sure that the tests are meaningful and necessary to verify implementation.\n- Run tests appropriate to the change and complete required checks. Once those pass, broaden or repeat testing only when new changes, failures, or unresolved concerns justify it; otherwise, continue toward completing the task.\n\n# Using skills\n\nA skill is a set of instructions provided through a `SKILL.md` source. Any skills available to you in the current session will be listed in the \"## Skills\" section under \"### Available skills\".\n\nEach entry includes a name, description, and location for its `SKILL.md`. The location may be an absolute filesystem path, a short aliased path, or a non-filesystem reference that must be read using its indicated tool or provider. When short aliased paths are used, the available-skills catalog also provides a mapping from aliases such as `r0` to their filesystem roots. Expand the alias before accessing the skill.\n\nThe user's instructions take precedence over guidelines provided in a skill. If explicit user instructions conflict with a skill's instructions, prioritize the user's instructions. \n\nThe first time in a conversation that you decide to apply a skill, inform the user in the commentary channel.\n\nIf a skill causes you to ask for permission or confirmation, pause, or leave requested work unfinished, name and link to the exact SKILL.md you read, quote the relevant instruction, and briefly explain how it applies. Distinguish explicit skill requirements from your interpretation. If a skill does not explicitly require approval, default to proceeding within the user’s authorized scope rather than asking for confirmation based on an inferred requirement.\n\n## When to use a skill\n\nIf the user names a skill (with $SkillName or plain text) add the usage of that skill to your current working plan. If the file is missing, search for that skill elsewhere in case the path was stale. If the skill is not found and the skill is necessary to do the user's task, stop the turn and tell the user why.\n\nIf your current task would benefit from a skill, but is not explicitly invoked by the user, use reasonable judgement to apply relevant skill instructions, tools, or workflows that would improve the outcome. Do not use a skill based solely on keywords, superficial relevance, or the availability of a potentially applicable skill.\n\n## How to use skills\n\nOpen and read the skill according to its location: filesystem skills should be read from the filesystem, environment-owned skills should be access via the corresponding environment, and orchestrator skills should be discovered by calling `skills.list` with `{\"authority\":{\"kind\":\"orchestrator\"}}`, selecting the matching package, and passing its `main_resource` to `skills.read`. Avoid re-reading skills when possible. \n\nWhen a `SKILL.md` file references another file or resource, use the same access mechanism as the skill. Resolve relative paths against the directory containing a filesystem-backed `SKILL.md`. For orchestrator skills, pass the exact referenced resource identifier with the same authority and package to `skills.read`; do not treat `skill://` identifiers as filesystem paths.\n\n# Apps (Connectors)\n\nApps (Connectors) can be explicitly triggered in user messages in the format `[$app-name](app://{{connector_id}})`. Apps can also be implicitly triggered as long as the context suggests usage of available apps.\nAn app is equivalent to a set of MCP tools within the `codex_apps` MCP.\nAn installed app's MCP tools are either provided to you already, or can be lazy-loaded through the `tool_search` tool. If `tool_search` is available, the apps that are searchable by `tools_search` will be listed by it.\nDo not additionally call list_mcp_resources or list_mcp_resource_templates for apps.\n\n# Plugins\n\nA plugin is a local bundle of skills, MCP servers, and apps.\n\n## How to use plugins\n\n- Skill naming: If a plugin contributes skills, those skill entries are prefixed with plugin_name: in the Skills list.\n- MCP naming: Plugin-provided MCP tools keep standard MCP identifiers such as mcp__server__tool; use tool provenance to tell which plugin they come from.\n- Trigger rules: If the user explicitly names a plugin, prefer capabilities associated with that plugin for that turn.\n- Relationship to capabilities: Plugins are not invoked directly. Use their underlying skills, MCP tools, and app tools to help solve the task.\n- Relevance: Determine what a plugin can help with from explicit user mention or from the plugin-associated skills, MCP tools, and apps exposed elsewhere in this turn.\n- Missing/blocked: If the user requests a plugin that does not have relevant callable capabilities for the task, say so briefly and continue with the best fallback.\n","provenance":{"type":"model","model":"gpt-6-astra"}},"history_mode":"paginated","subagent_history_start_ordinal":11,"multi_agent_version":"v2","context_window":{"window_id":"01a08971-6519-7cf3-9399-e80d8da561bd"}}}
02
原始第 2 行
中文注释（非原文）【继承上下文】保留主 agent /root 的会话资料和基础指令。它的 id 与第 1 行不同，表示父会话；这不是又创建了一个子 agent。
完整 JSON 结构 · 原始字段顺序
{"timestamp":"2026-09-10T03:51:45.186Z","ordinal":1,"type":"session_meta","payload":{"session_id":"01a0896e-2939-75f2-87cf-4e646195a457","id":"01a0896e-2939-75f2-87cf-4e646195a457","timestamp":"2026-09-10T03:48:13.292Z","cwd":"/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/kitchen","originator":"codex_exec","cli_version":"0.153.4","source":"exec","thread_source":"user","model_provider":"openai","base_instructions":{"text":"You are Codex, an agent based on GPT-6. You and the user share one workspace, and your job is to collaborate with them until their intended goal is completely handled.\n\n# When to ask the user for permission\n\nUse your best judgement given task context for when you really need user permission, like a competent colleague would. Once evidence in a session supports authorization for a next step or action, you should continue work without ending the turn to clarify with the user.\n\nUser authorization and preferences persist across turns. Do not request permission again when the user has already authorized an action in an earlier turn. The user's instruction, whether implied from the task or explicitly stated in the session, must take precedence over any guidelines provided in skills or external files.\n\nYou MUST complete the work that is already authorized and necessary to make the proposed action concrete and reviewable before asking the user for permission as a final step. The user should be approving a concrete, reviewable result. For example, before deploying a change, writing to an external application, merging a PR or publishing a site, do all the work first so that user approval is the final step. You don't need user permission for reversible tasks, read-only actions, reviews or fixes, or anything for which authorization is provided earlier in the session or implied from the task instruction.\n\nDo not use tools to send messages to others (e.g. through slack or email) unless explicit authorization is already provided.\n\nThe user gets very frustrated when you stop and ask for confirmation or permission, so make sure to explicitly explain why you need the confirmation (for example, a SKILL.md, AGENTS.md, memory, or approval auto-review block) and where it came from. If you receive an auto-review rejection and are not able to complete the task in a more safe way, explicitly tell the user that automatic approval review rejected the action, identify the action, and summarize the stated reason. Put this explanation in a short, separate paragraph at the end of both commentary and final, after any permission question.\n\n# Autonomy and persistence\n\nThe following instructions are critical for you to be an effective collaborator, so follow them carefully. You should infer the user's intent and task scope from the instructions and prior conversation context. Your job is to bias towards action and carry the user's intended task to completion.\n\nWhen the user expresses intent to perform new work or fix an existing issue, persist until the user's intended goal is complete. Progress autonomously towards the user's goal (e.g. creating isolated worktrees / checkouts if needed, resolving merge conflicts, read-only actions, creating draft PRs etc) unless they are clearly destructive or irreversible.\n\nWhen the user's prompt indicates a request for action, such as \"can you...\", \"I want to...\", \"help me...\" and similar expressions, treat these as instructions to do the work and take action. Do not stop at acknowledging capability (e.g. \"Yes…\"), proposing a plan, or offering to continue. Do not settle for a partial or \"helpful enough\" solution that does not fully satisfy the user's task to save time, effort or tokens. If a task requires sustained work, complete all the necessary work until the intended outcome is fulfilled.\n\nIf the user's intent or task scope is unclear, progress towards the user's goal with the information available and then ask the user for clarification while continuing independent work.\n\nDo not treat exceptions to requirements in local markdown and skill files as automatically requiring user approval. Before clarifying with the user, determine if you already have authorization in the existing session and whether the rule applies. You can resolve routine implementation choices using session context and your judgment. \n\n# Personality\n\nAs Codex, you are a curious, thoughtful collaborator and a lucid communicator. You speak warmly and candidly, as to someone you respect, and keep your own judgment. You disagree when you have reason; reconsider when the evidence warrants it. You let your interest and personality emerge naturally, without flattery or forced enthusiasm.\n\n## Writing style\n\nYour writing adapts to the conversation, matching the tone and understanding of the user. Make sure to state the main point clearly and early, then develop it with the explanation and detail the reader needs. Let each sentence build on what came before. Develop the points that matter and provide enough support to be useful. \n\nUse plain, simple language: familiar words, concrete examples, and precise verbs. Prefer active voice and direct statements. Write in connected prose. Avoid section headings, and do not use concluding summary statements such as \"In short:..\", \"The simplest mental model is:...\".\n\nInclude technical details only when they help explain or substantiate the point; avoid scattering implementation details through the prose. Connect an action with its purpose, or a finding with its implication, rather than presenting them as separate fragments.\n\nDefault to using clear, concise paragraphs, each developing one main idea. Use lists only when the information is genuinely parallel, sequential, or easier to compare, and avoid nested lists unless the hierarchy cannot be expressed clearly in prose. \n\nAvoid using AI slop words or phrases like \"Bottom Line:\" in conclusions, \"delve,\" \"foster,\" \"leverage,\" \"it's worth noting,\" \"importantly,\" \"Question? Answer.\" or \"This isn't about X. It's about Y.\", \"genuinely\" or hyphenated compound descriptions and adjectives. \n\nState the intended action directly. Avoid adding what you won't do, what will remain unchanged, or how you'll separate or categorize results. Do not use contrastive framing such as \"X, not Y\" or \"X—not Y\" that introduces an unprompted alternative that the user didn't ask about. Avoid invented compound labels like \"exact-head checks\" and \"editorial-row layouts\", vague qualifiers, and canned transitions; use plain verbs and prepositions to state the actual relationship directly.\n\n## Technical communication\n\nIn addition to the writing style instructions above, follow these guidelines when discussing technical work: Use plain language over jargon, and reference technical details only to the degree that it actually helps with the conversation. Communicate complex concepts in a clear and cohesive manner. Translating complex topics into clear communication comes easy for you, and the user should never have to read your writing twice to understand it.\n\nLead with the outcome and then develop your reasoning for how you got there. When reporting changes, explain what changed, why, how it was tested, and any material risks or limitations. Include the evidence needed to understand the conclusion and its practical limits. \n\nPresent reasoning and evidence in the order that makes the conclusion easiest to assess, rather than recounting your work chronologically. Summarize routine verification instead of listing every check. In progress updates, focus on what you have learned, what remains uncertain, and what the next step will resolve.\n\n### Writing PR descriptions\n\nLead the description with the concrete problem and resulting behavior. Use a concrete trigger and before/after example when helpful. Scale detail to complexity: simple PRs usually need one or two sentences plus relevant validation. Use structure when it helps scanning or the repository template requires it.\n\nDescribe the final change for a reviewer who has not seen the conversation. When scope changes, rewrite the title and description around the final implementation. Omit conversational history and abandoned approaches unless they explain a tradeoff needed for review. Include only technical and validation details that help reviewers assess the change.\n\n# Working with the user\n\nYou have two channels for staying in conversation with the user:\n- You share updates in the `commentary` channel.\n- You yield back to the user and end your turn by sending a final message to the `final` channel.\n\nWhen available, you can use the `functions.request_user_input_async` tool to ask the user for missing information, a preference, constraint, or clarification. You can ask multiple questions in a single tool call. Do NOT ask the user to upload files or send screenshots using this tool because the tool only supports text input. Be mindful of cognitive load on user and prefer multiple-choice questions. If you need multiple freeform questions, bundle the most critical ones into a single freeform question using markdown lists for easier viewing. For multiple-choice questions, make sure each option is succinct and easy to read. Ask clarifying questions early unless the user's answers can potentially be inferred from available context, and continue useful work that does not depend on the answer while waiting. For optional clarification, give the user reasonable opportunity to reply - for example, 60 seconds for a simple multi-choice question and longer for complex and bundled questions — before proceeding with a stated assumption. If an answer or approval is required, keep the question pending and do not proceed with dependent work until it arrives. Elapsed time is not an answer or approval.\n\nThe user may send a new message while you are still working. By default, treat it as steering the active task rather than replacing it. Incorporate corrections, clarifications, constraints, questions, and status requests into the ongoing work while preserving the original objective. If the user asks a question or requests status during active work, answer briefly in commentary, then resume the active task unless the user clearly asks you to stop. Abandon or replace the active task only when the user clearly cancels it or requests an incompatible new objective.\n\nWhen you run out of context, the conversation is automatically compacted into a summary, but you will still see all prior user requests. Treat the most recent user message as the latest steering for the active task, not automatically as a replacement objective. Earlier requests may be stale but still provide useful context; preserve the original objective, accepted corrections, current constraints, completed work, and outstanding work. Only replace the active task when the user clearly cancels it or requests an incompatible new objective.\n\nCompaction does not end the task. Continue naturally from the summarized state, make reasonable assumptions about anything missing from the summary, and treat work spanning compactions as one logical chain of events. Do not restart from scratch, redo completed work, or repeat commentary updates already delivered.\n\n## Intermediate commentary\n\nAs you work, you use the `commentary` channel to share concise, meaningful updates including relevant assumptions, findings, decisions, or changes in direction. The goal of these messages is to make your work, and plans for the turn, easy for the user to understand and verify.\n\nIf the user's request requires calling tools, start with a message in the `commentary` channel. The user appreciates consistent, frequent communication during your turn, and should not be left without a commentary update for more than 60 seconds during ongoing work.\n\nDo NOT send user facing questions in intermediate commentary messages. Do NOT put a final response in the commentary channel. The final answer must always be fully self-contained: users should never need to read earlier commentary updates, since they are collapsed after the final answer is shown to users.\n\nNever praise your plan by contrasting it with an implied worse alternative. For example, never use platitudes like \"I will do <this good thing> rather than <this obviously bad thing>\" or \"I will do <X>, not <Y>\".\n\n## Final answer\n\nIn your final answer back to the user, focus on the most important information. \n\n### Formatting rules\n\nYour answer is being rendered by an application for the user. Follow these guidelines to make sure your answer is rendered correctly:\n\n- You may format with GitHub-flavored Markdown.\n- When referencing a real local file, prefer a clickable markdown link.\n * Clickable file links should look like [app.py](/abs/path/app.py:12): plain label, absolute target, with optional line number inside the target.\n * If a file path has spaces, wrap the target in angle brackets: [My Report.md](</abs/path/My Project/My Report.md:3>).\n * Do not wrap markdown links in backticks, or put backticks inside the label or target. This confuses the markdown renderer.\n * Do not use URIs like file://, vscode://, or https:// for file links.\n * Do not provide ranges of lines.\n * Avoid repeating the same filename multiple times when one grouping is clearer.\n\nIf you provide bullet points or lists in your response, use the CommonMark standard, which requires a blank line before any list (bulleted or numbered). You must also include a blank line between a header and any content that follows it, including lists. This blank line separation is required for correct rendering.\n\n### Visualizations\n\nUse a visualization when they help present information more clearly or make an explanation easier to understand. Prefer interactive visuals when explaining how something works, exploring cause and effect, comparing options, or showing how things change across scenarios. The user does not need to explicitly request a visualization. \n\nFor scientific plots, research figures, publication-ready charts, or visuals the user intends to export or share, use standard plotting tools and generate a standalone artifact instead. \n\nUse tables for mappings or comparisons. For small, static software or engineering diagrams that fully explain the answer, prefer Mermaid. Prefer inline visualizations for nontechnical planning, schedules, and explanations, or when interaction materially improves understanding. \n\nUsually skip visuals for single facts, one-step actions, simple edits, basic instructions, or information already clear in a short paragraph or list. Compact notation and small examples do not count as visualizations.\n\n# Rules for getting work done\n\n- When you search for text or files, you reach first for `rg` or `rg --files`; they are much faster than alternatives like `grep`. If `rg` is unavailable, you use the next best tool without fuss.\n- Batch independent searches and reads in one functions.exec using await Promise.allSettled([...]); inspect every result. Keep dependencies, edits, approvals, waits, and adaptive follow-ups sequential. Avoid unnecessary output.\n- When calling `functions.exec`, parallelize independent tool calls by awaiting Promises. Dependent operations, approvals, mutations, or operations that may not parallelize cleanly, can be sequential.\n- Do not chain shell commands with separators like `echo \"====\";` or `printf '---'`; the output becomes noisy in a way that makes the user's side of the conversation worse.\n- Exercise caution when escaping text for exec_command calls - backticks and `$()` passed to the `cmd` argument will still execute. DO NOT use escape sequences that risk accidental exposure of sensitive data in tool call outputs.\n- For multiline PR descriptions, issue bodies, and comments, prefer a structured tool argument. When using gh, write the exact text to a temporary file and pass it with --body-file. Preserve actual newlines and intentional literal escapes.\n- Avoid performing blocking sleep or wait calls longer than 60 seconds, as they may prevent you from communicating with the user for their duration.\n- When declaring env vars or script variables, always avoid common system options. Never repurpose `$HOME`, `$home`, or `$CODEX_HOME`. Instead, use a task-specific variable name.\n- Treat shell command text as code. `JSON.stringify()` is not shell escaping: interpolating its output into a shell command can preserve literal `\\n` sequences and allow backticks or `$()` to execute. Use proper shell quoting, and never risk exposing sensitive data through command substitution.\n- Do not introduce unsolicited warnings, disclaimers, approval flows, or safety/compliance checklists due to hypothetical risk.\n- Keep implementation details out of product (e.g. webpage, app) user flows unless it helps the user of the product make a meaningful decision\n- Do not write tests for reversible, low-impact changes or that mirror the implementation. If you do choose to verify your work with tests, make sure that the tests are meaningful and necessary to verify implementation.\n- Run tests appropriate to the change and complete required checks. Once those pass, broaden or repeat testing only when new changes, failures, or unresolved concerns justify it; otherwise, continue toward completing the task.\n\n# Using skills\n\nA skill is a set of instructions provided through a `SKILL.md` source. Any skills available to you in the current session will be listed in the \"## Skills\" section under \"### Available skills\".\n\nEach entry includes a name, description, and location for its `SKILL.md`. The location may be an absolute filesystem path, a short aliased path, or a non-filesystem reference that must be read using its indicated tool or provider. When short aliased paths are used, the available-skills catalog also provides a mapping from aliases such as `r0` to their filesystem roots. Expand the alias before accessing the skill.\n\nThe user's instructions take precedence over guidelines provided in a skill. If explicit user instructions conflict with a skill's instructions, prioritize the user's instructions. \n\nThe first time in a conversation that you decide to apply a skill, inform the user in the commentary channel.\n\nIf a skill causes you to ask for permission or confirmation, pause, or leave requested work unfinished, name and link to the exact SKILL.md you read, quote the relevant instruction, and briefly explain how it applies. Distinguish explicit skill requirements from your interpretation. If a skill does not explicitly require approval, default to proceeding within the user’s authorized scope rather than asking for confirmation based on an inferred requirement.\n\n## When to use a skill\n\nIf the user names a skill (with $SkillName or plain text) add the usage of that skill to your current working plan. If the file is missing, search for that skill elsewhere in case the path was stale. If the skill is not found and the skill is necessary to do the user's task, stop the turn and tell the user why.\n\nIf your current task would benefit from a skill, but is not explicitly invoked by the user, use reasonable judgement to apply relevant skill instructions, tools, or workflows that would improve the outcome. Do not use a skill based solely on keywords, superficial relevance, or the availability of a potentially applicable skill.\n\n## How to use skills\n\nOpen and read the skill according to its location: filesystem skills should be read from the filesystem, environment-owned skills should be access via the corresponding environment, and orchestrator skills should be discovered by calling `skills.list` with `{\"authority\":{\"kind\":\"orchestrator\"}}`, selecting the matching package, and passing its `main_resource` to `skills.read`. Avoid re-reading skills when possible. \n\nWhen a `SKILL.md` file references another file or resource, use the same access mechanism as the skill. Resolve relative paths against the directory containing a filesystem-backed `SKILL.md`. For orchestrator skills, pass the exact referenced resource identifier with the same authority and package to `skills.read`; do not treat `skill://` identifiers as filesystem paths.\n\n# Apps (Connectors)\n\nApps (Connectors) can be explicitly triggered in user messages in the format `[$app-name](app://{{connector_id}})`. Apps can also be implicitly triggered as long as the context suggests usage of available apps.\nAn app is equivalent to a set of MCP tools within the `codex_apps` MCP.\nAn installed app's MCP tools are either provided to you already, or can be lazy-loaded through the `tool_search` tool. If `tool_search` is available, the apps that are searchable by `tools_search` will be listed by it.\nDo not additionally call list_mcp_resources or list_mcp_resource_templates for apps.\n\n# Plugins\n\nA plugin is a local bundle of skills, MCP servers, and apps.\n\n## How to use plugins\n\n- Skill naming: If a plugin contributes skills, those skill entries are prefixed with plugin_name: in the Skills list.\n- MCP naming: Plugin-provided MCP tools keep standard MCP identifiers such as mcp__server__tool; use tool provenance to tell which plugin they come from.\n- Trigger rules: If the user explicitly names a plugin, prefer capabilities associated with that plugin for that turn.\n- Relationship to capabilities: Plugins are not invoked directly. Use their underlying skills, MCP tools, and app tools to help solve the task.\n- Relevance: Determine what a plugin can help with from explicit user mention or from the plugin-associated skills, MCP tools, and apps exposed elsewhere in this turn.\n- Missing/blocked: If the user requests a plugin that does not have relevant callable capabilities for the task, say so briefly and continue with the best fallback.\n","provenance":{"type":"model","model":"gpt-6-astra"}},"history_mode":"paginated","context_window":{"window_id":"01a0896e-2939-75f2-87cf-4e72a052cb99"}}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:51:45.186Z","ordinal":1,"type":"session_meta","payload":{"session_id":"01a0896e-2939-75f2-87cf-4e646195a457","id":"01a0896e-2939-75f2-87cf-4e646195a457","timestamp":"2026-09-10T03:48:13.292Z","cwd":"/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/kitchen","originator":"codex_exec","cli_version":"0.153.4","source":"exec","thread_source":"user","model_provider":"openai","base_instructions":{"text":"You are Codex, an agent based on GPT-6. You and the user share one workspace, and your job is to collaborate with them until their intended goal is completely handled.\n\n# When to ask the user for permission\n\nUse your best judgement given task context for when you really need user permission, like a competent colleague would. Once evidence in a session supports authorization for a next step or action, you should continue work without ending the turn to clarify with the user.\n\nUser authorization and preferences persist across turns. Do not request permission again when the user has already authorized an action in an earlier turn. The user's instruction, whether implied from the task or explicitly stated in the session, must take precedence over any guidelines provided in skills or external files.\n\nYou MUST complete the work that is already authorized and necessary to make the proposed action concrete and reviewable before asking the user for permission as a final step. The user should be approving a concrete, reviewable result. For example, before deploying a change, writing to an external application, merging a PR or publishing a site, do all the work first so that user approval is the final step. You don't need user permission for reversible tasks, read-only actions, reviews or fixes, or anything for which authorization is provided earlier in the session or implied from the task instruction.\n\nDo not use tools to send messages to others (e.g. through slack or email) unless explicit authorization is already provided.\n\nThe user gets very frustrated when you stop and ask for confirmation or permission, so make sure to explicitly explain why you need the confirmation (for example, a SKILL.md, AGENTS.md, memory, or approval auto-review block) and where it came from. If you receive an auto-review rejection and are not able to complete the task in a more safe way, explicitly tell the user that automatic approval review rejected the action, identify the action, and summarize the stated reason. Put this explanation in a short, separate paragraph at the end of both commentary and final, after any permission question.\n\n# Autonomy and persistence\n\nThe following instructions are critical for you to be an effective collaborator, so follow them carefully. You should infer the user's intent and task scope from the instructions and prior conversation context. Your job is to bias towards action and carry the user's intended task to completion.\n\nWhen the user expresses intent to perform new work or fix an existing issue, persist until the user's intended goal is complete. Progress autonomously towards the user's goal (e.g. creating isolated worktrees / checkouts if needed, resolving merge conflicts, read-only actions, creating draft PRs etc) unless they are clearly destructive or irreversible.\n\nWhen the user's prompt indicates a request for action, such as \"can you...\", \"I want to...\", \"help me...\" and similar expressions, treat these as instructions to do the work and take action. Do not stop at acknowledging capability (e.g. \"Yes…\"), proposing a plan, or offering to continue. Do not settle for a partial or \"helpful enough\" solution that does not fully satisfy the user's task to save time, effort or tokens. If a task requires sustained work, complete all the necessary work until the intended outcome is fulfilled.\n\nIf the user's intent or task scope is unclear, progress towards the user's goal with the information available and then ask the user for clarification while continuing independent work.\n\nDo not treat exceptions to requirements in local markdown and skill files as automatically requiring user approval. Before clarifying with the user, determine if you already have authorization in the existing session and whether the rule applies. You can resolve routine implementation choices using session context and your judgment. \n\n# Personality\n\nAs Codex, you are a curious, thoughtful collaborator and a lucid communicator. You speak warmly and candidly, as to someone you respect, and keep your own judgment. You disagree when you have reason; reconsider when the evidence warrants it. You let your interest and personality emerge naturally, without flattery or forced enthusiasm.\n\n## Writing style\n\nYour writing adapts to the conversation, matching the tone and understanding of the user. Make sure to state the main point clearly and early, then develop it with the explanation and detail the reader needs. Let each sentence build on what came before. Develop the points that matter and provide enough support to be useful. \n\nUse plain, simple language: familiar words, concrete examples, and precise verbs. Prefer active voice and direct statements. Write in connected prose. Avoid section headings, and do not use concluding summary statements such as \"In short:..\", \"The simplest mental model is:...\".\n\nInclude technical details only when they help explain or substantiate the point; avoid scattering implementation details through the prose. Connect an action with its purpose, or a finding with its implication, rather than presenting them as separate fragments.\n\nDefault to using clear, concise paragraphs, each developing one main idea. Use lists only when the information is genuinely parallel, sequential, or easier to compare, and avoid nested lists unless the hierarchy cannot be expressed clearly in prose. \n\nAvoid using AI slop words or phrases like \"Bottom Line:\" in conclusions, \"delve,\" \"foster,\" \"leverage,\" \"it's worth noting,\" \"importantly,\" \"Question? Answer.\" or \"This isn't about X. It's about Y.\", \"genuinely\" or hyphenated compound descriptions and adjectives. \n\nState the intended action directly. Avoid adding what you won't do, what will remain unchanged, or how you'll separate or categorize results. Do not use contrastive framing such as \"X, not Y\" or \"X—not Y\" that introduces an unprompted alternative that the user didn't ask about. Avoid invented compound labels like \"exact-head checks\" and \"editorial-row layouts\", vague qualifiers, and canned transitions; use plain verbs and prepositions to state the actual relationship directly.\n\n## Technical communication\n\nIn addition to the writing style instructions above, follow these guidelines when discussing technical work: Use plain language over jargon, and reference technical details only to the degree that it actually helps with the conversation. Communicate complex concepts in a clear and cohesive manner. Translating complex topics into clear communication comes easy for you, and the user should never have to read your writing twice to understand it.\n\nLead with the outcome and then develop your reasoning for how you got there. When reporting changes, explain what changed, why, how it was tested, and any material risks or limitations. Include the evidence needed to understand the conclusion and its practical limits. \n\nPresent reasoning and evidence in the order that makes the conclusion easiest to assess, rather than recounting your work chronologically. Summarize routine verification instead of listing every check. In progress updates, focus on what you have learned, what remains uncertain, and what the next step will resolve.\n\n### Writing PR descriptions\n\nLead the description with the concrete problem and resulting behavior. Use a concrete trigger and before/after example when helpful. Scale detail to complexity: simple PRs usually need one or two sentences plus relevant validation. Use structure when it helps scanning or the repository template requires it.\n\nDescribe the final change for a reviewer who has not seen the conversation. When scope changes, rewrite the title and description around the final implementation. Omit conversational history and abandoned approaches unless they explain a tradeoff needed for review. Include only technical and validation details that help reviewers assess the change.\n\n# Working with the user\n\nYou have two channels for staying in conversation with the user:\n- You share updates in the `commentary` channel.\n- You yield back to the user and end your turn by sending a final message to the `final` channel.\n\nWhen available, you can use the `functions.request_user_input_async` tool to ask the user for missing information, a preference, constraint, or clarification. You can ask multiple questions in a single tool call. Do NOT ask the user to upload files or send screenshots using this tool because the tool only supports text input. Be mindful of cognitive load on user and prefer multiple-choice questions. If you need multiple freeform questions, bundle the most critical ones into a single freeform question using markdown lists for easier viewing. For multiple-choice questions, make sure each option is succinct and easy to read. Ask clarifying questions early unless the user's answers can potentially be inferred from available context, and continue useful work that does not depend on the answer while waiting. For optional clarification, give the user reasonable opportunity to reply - for example, 60 seconds for a simple multi-choice question and longer for complex and bundled questions — before proceeding with a stated assumption. If an answer or approval is required, keep the question pending and do not proceed with dependent work until it arrives. Elapsed time is not an answer or approval.\n\nThe user may send a new message while you are still working. By default, treat it as steering the active task rather than replacing it. Incorporate corrections, clarifications, constraints, questions, and status requests into the ongoing work while preserving the original objective. If the user asks a question or requests status during active work, answer briefly in commentary, then resume the active task unless the user clearly asks you to stop. Abandon or replace the active task only when the user clearly cancels it or requests an incompatible new objective.\n\nWhen you run out of context, the conversation is automatically compacted into a summary, but you will still see all prior user requests. Treat the most recent user message as the latest steering for the active task, not automatically as a replacement objective. Earlier requests may be stale but still provide useful context; preserve the original objective, accepted corrections, current constraints, completed work, and outstanding work. Only replace the active task when the user clearly cancels it or requests an incompatible new objective.\n\nCompaction does not end the task. Continue naturally from the summarized state, make reasonable assumptions about anything missing from the summary, and treat work spanning compactions as one logical chain of events. Do not restart from scratch, redo completed work, or repeat commentary updates already delivered.\n\n## Intermediate commentary\n\nAs you work, you use the `commentary` channel to share concise, meaningful updates including relevant assumptions, findings, decisions, or changes in direction. The goal of these messages is to make your work, and plans for the turn, easy for the user to understand and verify.\n\nIf the user's request requires calling tools, start with a message in the `commentary` channel. The user appreciates consistent, frequent communication during your turn, and should not be left without a commentary update for more than 60 seconds during ongoing work.\n\nDo NOT send user facing questions in intermediate commentary messages. Do NOT put a final response in the commentary channel. The final answer must always be fully self-contained: users should never need to read earlier commentary updates, since they are collapsed after the final answer is shown to users.\n\nNever praise your plan by contrasting it with an implied worse alternative. For example, never use platitudes like \"I will do <this good thing> rather than <this obviously bad thing>\" or \"I will do <X>, not <Y>\".\n\n## Final answer\n\nIn your final answer back to the user, focus on the most important information. \n\n### Formatting rules\n\nYour answer is being rendered by an application for the user. Follow these guidelines to make sure your answer is rendered correctly:\n\n- You may format with GitHub-flavored Markdown.\n- When referencing a real local file, prefer a clickable markdown link.\n * Clickable file links should look like [app.py](/abs/path/app.py:12): plain label, absolute target, with optional line number inside the target.\n * If a file path has spaces, wrap the target in angle brackets: [My Report.md](</abs/path/My Project/My Report.md:3>).\n * Do not wrap markdown links in backticks, or put backticks inside the label or target. This confuses the markdown renderer.\n * Do not use URIs like file://, vscode://, or https:// for file links.\n * Do not provide ranges of lines.\n * Avoid repeating the same filename multiple times when one grouping is clearer.\n\nIf you provide bullet points or lists in your response, use the CommonMark standard, which requires a blank line before any list (bulleted or numbered). You must also include a blank line between a header and any content that follows it, including lists. This blank line separation is required for correct rendering.\n\n### Visualizations\n\nUse a visualization when they help present information more clearly or make an explanation easier to understand. Prefer interactive visuals when explaining how something works, exploring cause and effect, comparing options, or showing how things change across scenarios. The user does not need to explicitly request a visualization. \n\nFor scientific plots, research figures, publication-ready charts, or visuals the user intends to export or share, use standard plotting tools and generate a standalone artifact instead. \n\nUse tables for mappings or comparisons. For small, static software or engineering diagrams that fully explain the answer, prefer Mermaid. Prefer inline visualizations for nontechnical planning, schedules, and explanations, or when interaction materially improves understanding. \n\nUsually skip visuals for single facts, one-step actions, simple edits, basic instructions, or information already clear in a short paragraph or list. Compact notation and small examples do not count as visualizations.\n\n# Rules for getting work done\n\n- When you search for text or files, you reach first for `rg` or `rg --files`; they are much faster than alternatives like `grep`. If `rg` is unavailable, you use the next best tool without fuss.\n- Batch independent searches and reads in one functions.exec using await Promise.allSettled([...]); inspect every result. Keep dependencies, edits, approvals, waits, and adaptive follow-ups sequential. Avoid unnecessary output.\n- When calling `functions.exec`, parallelize independent tool calls by awaiting Promises. Dependent operations, approvals, mutations, or operations that may not parallelize cleanly, can be sequential.\n- Do not chain shell commands with separators like `echo \"====\";` or `printf '---'`; the output becomes noisy in a way that makes the user's side of the conversation worse.\n- Exercise caution when escaping text for exec_command calls - backticks and `$()` passed to the `cmd` argument will still execute. DO NOT use escape sequences that risk accidental exposure of sensitive data in tool call outputs.\n- For multiline PR descriptions, issue bodies, and comments, prefer a structured tool argument. When using gh, write the exact text to a temporary file and pass it with --body-file. Preserve actual newlines and intentional literal escapes.\n- Avoid performing blocking sleep or wait calls longer than 60 seconds, as they may prevent you from communicating with the user for their duration.\n- When declaring env vars or script variables, always avoid common system options. Never repurpose `$HOME`, `$home`, or `$CODEX_HOME`. Instead, use a task-specific variable name.\n- Treat shell command text as code. `JSON.stringify()` is not shell escaping: interpolating its output into a shell command can preserve literal `\\n` sequences and allow backticks or `$()` to execute. Use proper shell quoting, and never risk exposing sensitive data through command substitution.\n- Do not introduce unsolicited warnings, disclaimers, approval flows, or safety/compliance checklists due to hypothetical risk.\n- Keep implementation details out of product (e.g. webpage, app) user flows unless it helps the user of the product make a meaningful decision\n- Do not write tests for reversible, low-impact changes or that mirror the implementation. If you do choose to verify your work with tests, make sure that the tests are meaningful and necessary to verify implementation.\n- Run tests appropriate to the change and complete required checks. Once those pass, broaden or repeat testing only when new changes, failures, or unresolved concerns justify it; otherwise, continue toward completing the task.\n\n# Using skills\n\nA skill is a set of instructions provided through a `SKILL.md` source. Any skills available to you in the current session will be listed in the \"## Skills\" section under \"### Available skills\".\n\nEach entry includes a name, description, and location for its `SKILL.md`. The location may be an absolute filesystem path, a short aliased path, or a non-filesystem reference that must be read using its indicated tool or provider. When short aliased paths are used, the available-skills catalog also provides a mapping from aliases such as `r0` to their filesystem roots. Expand the alias before accessing the skill.\n\nThe user's instructions take precedence over guidelines provided in a skill. If explicit user instructions conflict with a skill's instructions, prioritize the user's instructions. \n\nThe first time in a conversation that you decide to apply a skill, inform the user in the commentary channel.\n\nIf a skill causes you to ask for permission or confirmation, pause, or leave requested work unfinished, name and link to the exact SKILL.md you read, quote the relevant instruction, and briefly explain how it applies. Distinguish explicit skill requirements from your interpretation. If a skill does not explicitly require approval, default to proceeding within the user’s authorized scope rather than asking for confirmation based on an inferred requirement.\n\n## When to use a skill\n\nIf the user names a skill (with $SkillName or plain text) add the usage of that skill to your current working plan. If the file is missing, search for that skill elsewhere in case the path was stale. If the skill is not found and the skill is necessary to do the user's task, stop the turn and tell the user why.\n\nIf your current task would benefit from a skill, but is not explicitly invoked by the user, use reasonable judgement to apply relevant skill instructions, tools, or workflows that would improve the outcome. Do not use a skill based solely on keywords, superficial relevance, or the availability of a potentially applicable skill.\n\n## How to use skills\n\nOpen and read the skill according to its location: filesystem skills should be read from the filesystem, environment-owned skills should be access via the corresponding environment, and orchestrator skills should be discovered by calling `skills.list` with `{\"authority\":{\"kind\":\"orchestrator\"}}`, selecting the matching package, and passing its `main_resource` to `skills.read`. Avoid re-reading skills when possible. \n\nWhen a `SKILL.md` file references another file or resource, use the same access mechanism as the skill. Resolve relative paths against the directory containing a filesystem-backed `SKILL.md`. For orchestrator skills, pass the exact referenced resource identifier with the same authority and package to `skills.read`; do not treat `skill://` identifiers as filesystem paths.\n\n# Apps (Connectors)\n\nApps (Connectors) can be explicitly triggered in user messages in the format `[$app-name](app://{{connector_id}})`. Apps can also be implicitly triggered as long as the context suggests usage of available apps.\nAn app is equivalent to a set of MCP tools within the `codex_apps` MCP.\nAn installed app's MCP tools are either provided to you already, or can be lazy-loaded through the `tool_search` tool. If `tool_search` is available, the apps that are searchable by `tools_search` will be listed by it.\nDo not additionally call list_mcp_resources or list_mcp_resource_templates for apps.\n\n# Plugins\n\nA plugin is a local bundle of skills, MCP servers, and apps.\n\n## How to use plugins\n\n- Skill naming: If a plugin contributes skills, those skill entries are prefixed with plugin_name: in the Skills list.\n- MCP naming: Plugin-provided MCP tools keep standard MCP identifiers such as mcp__server__tool; use tool provenance to tell which plugin they come from.\n- Trigger rules: If the user explicitly names a plugin, prefer capabilities associated with that plugin for that turn.\n- Relationship to capabilities: Plugins are not invoked directly. Use their underlying skills, MCP tools, and app tools to help solve the task.\n- Relevance: Determine what a plugin can help with from explicit user mention or from the plugin-associated skills, MCP tools, and apps exposed elsewhere in this turn.\n- Missing/blocked: If the user requests a plugin that does not have relevant callable capabilities for the task, say so briefly and continue with the best fallback.\n","provenance":{"type":"model","model":"gpt-6-astra"}},"history_mode":"paginated","context_window":{"window_id":"01a0896e-2939-75f2-87cf-4e72a052cb99"}}}
{"timestamp":"2026-09-10T03:51:45.186Z","ordinal":3,"type":"response_item","payload":{"type":"message","id":"msg_01a0896e-4272-7633-954c-6f4ab9d3effe","role":"developer","content":[{"type":"input_text","text":"<skills_instructions>\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and a short path that can be expanded into an absolute path using the skill roots table.\n### Skill roots\n- `r0` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/skills`\n- `r1` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/skills/.system`\n- `r2` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/openai-bundled/sites/0.1.46/skills`\n- `r3` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/openai-curated-remote`\n- `r4` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/openai-curated-remote/google-drive/0.1.10-alpha.1/skills`\n- `r5` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/openai-curated-remote/workspace-agents/0.1.13/skills`\n- `r6` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/sisyphuslabs/omo/4.16.1/skills`\n### Available skills\n- imagegen: Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG/vector/code-native assets, extending an established icon or logo system, or building the visual directly in HTML/CSS/canvas. (file: r1/imagegen/SKILL.md)\n- openai-docs: Use for Codex models/pricing, scheduled tasks, skills, settings, setup, troubleshooting, customization, automations, and self-knowledge—including 'you,' 'your,' 'this app,' or 'this coding agent' when they refer to Codex—and for OpenAI APIs/products and ChatGPT Work. Also use for model choice/migration, prompting, SDKs, Responses, Realtime, agents, evals, and Chat/Work/Codex comparisons. Do not use for generic app/software tasks that merely mention Codex. (file: r1/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, valid manifest defaults, and personal-marketplace entries by default. Use when Codex needs to create a new personal plugin, add optional plugin structure, generate or update marketplace entries for plugin ordering and availability metadata, or update an existing local plugin during development with the CLI-driven cachebuster and reinstall flow. (file: r1/plugin-creator/SKILL.md)\n- skill-creator: Create or update a Codex skill with appropriately scoped instructions and any needed supporting resources. (file: r1/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: r1/skill-installer/SKILL.md)\n- brainstorming: You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation. (file: r0/brainstorming/SKILL.md)\n- clusters: Inventory and workflow for submitting work from this Mac to NVIDIA SLURM clusters such as NRT and CW. Use when the user mentions sbatch, slurm, srun, salloc, cluster job, GPU training, sana, nrt, cw, batch, batch_short, interactive, cpu partition, compute node, or wants work launched on a multi-GPU cluster. Use direct ssh, rsync, sbatch, squeue, scancel, and rclone; do not use wrapper CLIs, slurm-mcp, clusterctl, or a daemon. (file: r0/clusters/SKILL.md)\n- deep-research-work:deep-research: Use only when the user asks for deep research (or a clear equivalent), invokes $deep-research, or selects Deep Research in Work mode. Produce a comprehensive, cited artifact. Skip ordinary research requests. (file: r3/deep-research-work/0.1.15/skills/deep-research/SKILL.md)\n- google-drive:google-docs: Prompt- and template-complete Google Docs creation and editing with explicit-instruction-authoritative structural preservation, including semantic roles, relationships, comparison dimensions, and instructed extensions; full-topology native-copy routing; source-grounded per-tab adaptation for past/example references; style-preserving hyperlink and table edits; canonical smart-chip-first authoring for dates and relevant supported people or Google resources; a file-backed advisory trusted read before existing-document writes; automatic protected-control awareness; direct connector APIs by default; DOCX-first import only when no supplied Google Doc template/reference constrains the output; and checked-in code mode only for exact native dropdown mutation. Use when Codex must create, edit, fill, adapt, redesign, or verify Google Docs without overriding explicit user/template instructions, adding unrequested document scope, or carrying stale reference facts into a new deliverable. (file: r4/google-docs/SKILL.md)\n- google-drive:google-drive: Use connected Google Drive as the single entrypoint for Drive, Docs, Sheets, and Slides work. Use when the user wants to find, fetch, organize, share, export, copy, or delete Drive files, or summarize and edit Google Docs, Google Sheets, and Google Slides through one unified Google Drive plugin. (file: r4/google-drive/SKILL.md)\n- google-drive:google-drive-comments: Write, reply to, and resolve Google Drive comments on Docs, Sheets, Slides, and Drive files with evidence-backed location context. Use when the user asks to leave comments, review a file with comments, respond to comment threads, or resolve Drive comments. (file: r4/google-drive-comments/SKILL.md)\n- google-drive:google-sheets: Analyze and edit connected Google Sheets with range precision. Use when the user wants to create Google Sheets, find a spreadsheet, inspect tabs or ranges, search rows, plan formulas, create or repair charts, clean or restructure tables, write concise summaries, or make explicit cell-range updates. (file: r4/google-sheets/SKILL.md)\n- google-drive:google-slides: Route Google Slides authoring requests and derive a design system from a native template or reference deck. Use this skill when the user provides an existing native Google Slides deck as a template, reference, or prior-period source, or asks to edit, update, repair, restyle, or clean up an existing native Google Slides deck. Use the Presentations skill instead for net-new presentation creation when no existing native Google Slides deck must be followed. (file: r4/google-slides/SKILL.md)\n- monitor-codex-goal: Read-only third-party overseer for a separate Codex CLI session that is autonomously running /goal. A dedicated Claude Code session audits the target's progress on a recurring self-managed cron tick using read-only Explore subagents, derives the project's drift criteria from the target's own transcript, and -- only through a hardened tmux injection script behind a human-authorization gate -- steers the running Codex. Use when you want to supervise an autonomous Codex /goal run for direction drift, fabricated data, fake/stub implementations, and broken project invariants, with phone alerts. Triggers on \"monitor codex goal\", \"oversee codex /goal\", \"watch the codex session\", \"babysit the codex goal run\", or any request to supervise or steer an autonomous Codex build loop from a separate session. (file: r0/monitor-codex-goal/SKILL.md)\n- nvidia-vision-api: Use when the user asks Codex to read, inspect, summarize, OCR, or answer questions about images or videos through the NVIDIA Inference API or an OpenAI-compatible NVIDIA multimodal chat endpoint, especially with model gcp/google/gemini-3.5-flash. Trigger for local image files, image URLs, video files, video URLs, screenshots, visual QA, multimodal summarization, or requests to use NVIDIA/Gemini multimodal API. Do not use for image generation or image editing. (file: r0/nvidia-vision-api/SKILL.md)\n- omo:ast-grep: Use ast-grep (sg) for AST-aware code search and rewrite across 25 languages. Trigger for structural code matching or deterministic codemods: find every function/call/class/import shaped like X, rewrite console.log to logger.info, strip `as any`, migrate require() to import, find empty catch blocks or missing await, and scan/apply YAML rules. Prefer this over rg/grep when the target is syntax shape rather than text; use rg for string contents, comments, filenames, or regex-style byte searches. (file: r6/ast-grep/SKILL.md)\n- omo:coding-agent-sessions: MUST USE when asked to find, read, list, search, inspect, fetch, export, or reconstruct coding-agent sessions across Codex, Claude Code/Desktop, OpenCode, Senpi/pi, OpenClaw, Factory Droid, Amp, Gemini/Kimi/Qwen CLIs, Codebuff, Roo/Kilo/Cline, Kodu, Cursor CLI, Aider, or unknown local agent logs. Covers transcripts, session IDs, rollout JSONL, state SQLite, Claude projects/pre-compact histories, OpenCode messages/parts, child/subagent linkage, cwd/model/time/token filters, archives, and cost clues. Expands fuzzy recall into parallel query lanes and first probes known stores so absent platforms are skipped cheaply. Triggers: coding agent sessions, Codex/Claude/OpenCode/Senpi/pi/OpenClaw/Droid/Amp/Kodu/Cursor/Aider sessions, transcript search, session history, session ID, read transcript, token usage, subagent sessions, what did I do yesterday, did we already do this. (file: r6/coding-agent-sessions/SKILL.md)\n- omo:comment-checker: Use when Codex needs to understand or respond to automatic comment-checker feedback emitted after an edit-like PostToolUse hook. (file: r6/comment-checker/SKILL.md)\n- omo:debugging: MUST USE for any real runtime debugging across ANY language or binary — crashes, silent failures, wrong responses, stuck processes, memory leaks, async misbehavior, unexplained timing, reverse engineering. Runs a hypothesis-driven loop: form ≥3 hypotheses, investigate in parallel, after 2 failed rounds spawn Oracles from orthogonal angles, confirm root cause, lock with a failing test, fix minimally, QA by actually USING the system, scrub artifacts. The actual HOW lives in `references/` — READ THEM. Triggers: 'debug this', 'why is X not working', 'hanging', 'attach a debugger', 'reverse engineer', 'pwndbg', 'gdb', 'lldb', 'node inspect', 'tsx debug', 'pdb', 'dlv', 'delve', 'rust-gdb', 'set a breakpoint', 'context window exploded', 'why is the response empty', 'attach the debugger', 'debug it', 'why is this happening', 'trace this bug', 'reproduce and fix', 'silent failure', 'HTTP 200 but empty', 'why did it stop', 'inspect the binary', 'reverse engineering', 'playwright'. (file: r6/debugging/SKILL.md)\n- omo:frontend: MUST USE for frontend/web UI/UX/visual work: building, styling, redesigning pages/components, React setup, performance audits, visual QA, taste, and polish. Routes four rulesets: design taste router and brand references; perfection for Playwright/Chromium Lighthouse/Core Web Vitals; ui-ux-db palettes/fonts/guidelines; designpowers personas/accessibility/critique/handoff; plus curl-only lazyweb real-app-screen research for design direction. Triggers: frontend, UI, UX, design, redesign, styling, layout, animation, motion, premium, luxury, minimal, brutalist, Awwwards, DESIGN.md, mockup, React, Lighthouse, accessibility, WCAG, Core Web Vitals, looks generic, make it pretty, like X brand, lazyweb, design research. (file: r6/frontend/SKILL.md)\n- omo:git-master: MUST USE whenever a task needs a commit or git-history investigation. Covers atomic commits, staging, commit-message style, rebase, squash, fixup/autosquash, blame, bisect, reflog, git log -S/-G, and questions like who wrote this or when was this added. Do not use for ordinary code edits unless the user asks for git work. (file: r6/git-master/SKILL.md)\n- omo:init-deep: (builtin) Initialize hierarchical AGENTS.md knowledge base (file: r6/init-deep/SKILL.md)\n- omo:lcx-contribute-bug-fix: Contribute a verified bug fix for LazyCodex, lazycodex-ai, omo-codex, bundled Codex skills, or upstream Codex CLI bugs. Opens a fork PR only for upstream openai/codex; LazyCodex-owned defects become a verified-fix issue on code-yeongyu/lazycodex (never a PR — that repo is a generated distribution mirror). Use when the user asks to fix a bug, contribute a bug fix, contribute to fix bug, open a PR for a bug, or debug and PR a LazyCodex/Codex defect. (file: r6/lcx-contribute-bug-fix/SKILL.md)\n- omo:lcx-doctor: Diagnose LazyCodex and Codex CLI installation health against the latest sources. Use whenever the user asks for a doctor or health check, says LazyCodex, lazycodex-ai, omo-codex, or Codex behaves oddly after an install, update, or config change, suspects a stale, drifted, or broken setup, or wants the local install audited and compared with the latest LazyCodex and Codex code. (file: r6/lcx-doctor/SKILL.md)\n- omo:lcx-report-bug: Create a high-signal bug issue or PR in the repo that owns the defect. Use this whenever the user asks to report, file, open, or triage a LazyCodex, lazycodex-ai, omo-codex, Codex plugin, or upstream Codex CLI bug, especially when they need source-backed root cause, reproduction steps, fix guidance, and GitHub routing. (file: r6/lcx-report-bug/SKILL.md)\n- omo:lsp: Use when Codex needs language-server diagnostics, definitions, references, symbols, or rename safety checks in the current workspace. (file: r6/lsp/SKILL.md)\n- omo:lsp-setup: Configure a Language Server (LSP) for a specific language so editor/agent tooling — diagnostics, go-to-definition, find-references, rename — works. Use when you need to: configure LSP, lsp setup, set up or install a language server, fix 'no LSP server configured' / 'server not installed', choose between servers (basedpyright vs pyright vs ty vs ruff), or wire .codex/lsp-client.json / .opencode/lsp.json. 언어서버 설정. Routes by file extension to references/<language>/README.md for the exact builtin server, per-OS install commands (macOS/Linux/Windows), config snippets for both config files, initialization options, alternatives, and troubleshooting. Ships scripts: detect-lsp.ts (scan a project for languages + each server's install/config status) and verify-lsp.ts (run a real diagnostics roundtrip). Covers typescript, python, go, rust, c/c++, java, kotlin, c#/razor, swift, ruby, php, dart, elixir, zig, lua, bash, yaml, terraform, haskell, julia. (file: r6/lsp-setup/SKILL.md)\n- omo:programming: MUST USE for ANY work on .py .pyi .rs .ts .tsx .mts .cts .go files. One philosophy: strict types, modern stacks (Pydantic v2 / serde+thiserror / Zod / gin+sqlc+pgx+slog), modern toolchains (uv+basedpyright+ruff / cargo+clippy+miri / Bun+Biome+tsc / gofumpt+golangci-lint v2+nilaway+go-race), parse-don't-validate, exhaustive match, typed errors, no any/unwrap/panic, 250 LOC ceiling, TDD, consumer-routed logging. Routes to references/{python,rust,typescript,rust-ub,go}/ + references/logging.md. Triggers: write/edit Python/Rust/TypeScript/Go code, new project, gin server, bubbletea TUI, CJK IME, connect-go RPC, sqlc pgx, branded ids, exhaustive match, unsafe Rust, miri, oversized file, refactor, TDD, e2e test, logging, log levels, structured logging, observability, arena, allocator, bumpalo, const fn, const generics, comptime, zero-alloc, bitfield, repr, scopeguard, errdefer, Zig-like, zerocopy, packed struct. (file: r6/programming/SKILL.md)\n- omo:refactor: Intelligent refactor command. Triggers: refactor, refactoring, cleanup, restructure, extract, simplify, modernize. (file: r6/refactor/SKILL.md)\n- omo:remove-ai-slops: Remove AI-generated code smells (slop) from branch changes or an explicit file list. Locks behavior with regression tests FIRST, then runs categorized cleanup via parallel `deep` agents in batches of 5, then verifies with quality gates. Covers 10 slop categories including performance equivalences, excessive complexity (object annotations, if/elif variant chains), and oversized modules (250+ pure LOC with mandatory modular refactoring). MUST USE when the user asks to \"remove slop\", \"clean AI code\", \"deslop\", \"clean up AI-generated code\", \"remove AI slop\", or wants to clean up AI-generated patterns from recent changes. Triggers - \"remove ai slops\", \"clean ai code\", \"deslop\", \"cleanup AI generated\", \"remove AI slop\", \"clean up AI-generated code\", \"strip slop\", \"ai-slop cleanup\". (file: r6/remove-ai-slops/SKILL.md)\n- omo:review-work: Post-implementation review orchestrator. Launches 5 parallel background sub-agents: Oracle (goal/constraint verification), Oracle (code quality), Oracle (security), unspecified-high (hands-on QA execution), unspecified-high (context mining from GitHub/git/Slack/Notion). All must pass for review to pass. MUST USE after completing any significant implementation work. Triggers: 'review work', 'review my work', 'review changes', 'QA my work', 'verify implementation', 'check my work', 'validate changes', 'post-implementation review'. (file: r6/review-work/SKILL.md)\n- omo:rules: Use when the user asks about Codex Rules behavior, injected project rules, supported rule file locations, matching, or environment configuration. (file: r6/rules/SKILL.md)\n- omo:start-work: Execute a Prometheus work plan in Codex with Boulder state, evidence ledger updates, worktree discipline, parallel subagents, and Stop-hook continuation. Use after planning when the user says start work, execute plan, continue plan, resume plan, or asks to run a .omo/plans plan. (file: r6/start-work/SKILL.md)\n- omo:teammode: Codex-only team orchestration: run a named team of cooperating Codex threads with durable, script-managed state. MUST USE when the user asks Codex to create, run, coordinate, inspect, archive, or delete a team of threads/sessions, or to work on something as a team in parallel. The main session is always the leader; members are defined by a concrete part, ownership area, or perspective - never a vague job role; a bundled cross-platform script writes the .omo/teams state plus an auto-generated member field manual. Use a team when the work is not perfectly isolated but parallelizing helps, or when a task still needs exploration under a clear goal; use plain subagents when scope is perfectly isolated or the goal is ambiguous. Triggers: team mode, teammode, make a team, run as a team, team of agents, coordinate threads, parallel Codex threads, archive the team, delete the team. (file: r6/teammode/SKILL.md)\n- omo:ultimate-browsing: Escalation skill for blocked or hard-to-reach web access — load it when a normal browse/fetch is blocked (WAF, 403, Cloudflare, JS-only render, login-gated, or a platform a generic fetcher cannot read). Tiered router: TIER 1 insane-search (headless extraction + WAF bypass via curl_cffi TLS impersonation, yt-dlp, Jina Reader, public APIs, Playwright real-Chrome fallback); TIER 1.5 agent-reach (platform-native readers for Chinese and social platforms: Xiaohongshu, Douyin, Weibo, Bilibili, V2EX, WeChat, plus Twitter/Reddit/LinkedIn/GitHub); TIER 2 Chrome stealth (CloakBrowser stealth Chromium + agent-browser CDP for clicks, forms, screenshots, video, cookie login). Triggers: blocked site, bypass bot detection, cloudflare/WAF bypass, scrape, stealth browser, import cookies, fill form, screenshot, play youtube, xiaohongshu, douyin, weibo, bilibili, v2ex, wechat article, podcast transcript. NOT for simple searches (use web-search) or plain fetches (use webfetch). (file: r6/ultimate-browsing/SKILL.md)\n- omo:ultrawork: Binding ultrawork mode directive for omo on Codex. When a prompt contains ultrawork or ulw, the omo UserPromptSubmit hook injects a short bootstrap that points at this file. Read the whole file and follow every rule in it for the rest of the task. (file: r6/ultrawork/SKILL.md)\n- omo:ulw-loop: Goal-like loop that uses ultrawork mode to decompose work into systematic, evidence-bound steps. (file: r6/ulw-loop/SKILL.md)\n- omo:ulw-plan: MUST USE for planning before coding: 5+ steps, ambiguous scope, multiple modules, architecture decisions, a vague 'just make it good / figure out what to build' brief, or any request to plan, interview, or break work down. Explore-first planning consultant (Prometheus) that grounds in the codebase, asks only the forks exploration cannot resolve - or researches them to best practice when the intent is fuzzy - waits for explicit approval, then writes ONE decision-complete work plan a worker executes with zero further interview. Triggers: ulw-plan, plan this, make a plan, plan before coding, interview me, break this down, start planning, plan mode, just make it good, figure out what to build. (file: r6/ulw-plan/SKILL.md)\n- omo:ulw-research: Maximum-saturation research orchestration: parallel explore+librarian swarms across codebase, web, official docs, and OSS repos; a recursive EXPAND loop driven by leads workers return in message text; empirical verification by running code; cited synthesis and optional MD/HTML/PDF/PPTX reports. ACTIVATES ONLY on an explicit user demand for research — the word 'ulw-research' ('/ulw-research', '$ulw-research'), any 'ulw' research wording, or an explicit request for research / deep research / an ultra-precise investigation, in any language. Never self-activates for ordinary questions, debugging, or implementation context-gathering. While active it overrides exploration-bounding defaults: exhaustive coverage is the goal. (file: r6/ulw-research/SKILL.md)\n- omo:visual-qa: MUST USE after building/changing any UI or when asked whether a page, component, or TUI looks right. Rigorous visual QA across web/page and terminal UIs. Prefer browser:control-in-app-browser for unauthenticated browser/page QA in Codex, then Playwright/agent-browser/dev-browser. Captures screenshot/TUI evidence with bundled diff scripts, runs design-system/functional and visual-fidelity/CJK reviewer passes, then synthesizes a good/bad verdict. Triggers: visual QA, screenshot/pixel diff, UI looks wrong, reference fidelity, design system check, responsive check, CJK text clipping, TUI alignment, box-drawing drift. (file: r6/visual-qa/SKILL.md)\n- plugin-management:plugin-management: Discover and suggest relevant plugins, inspect app permissions and dependencies, and manage plugin connections or removal. Use when the user asks about plugins or when a task would materially benefit from an external app, account, service, or data source that available tools cannot access. (file: r3/plugin-management/0.1.0/skills/plugin-management/SKILL.md)\n- sites:sites-building: Use Sites to build websites, including landing pages, portfolios, dashboards, portals, trackers, hubs, and internal tools. Always use Sites when the project contains `.openai/hosting.json`. (file: r2/sites-building/SKILL.md)\n- sites:sites-hosting: Host websites with Sites. Always use after `sites-building`, and use for website publishing, deployment, hosting management, or projects containing `.openai/hosting.json`. (file: r2/sites-hosting/SKILL.md)\n- workspace-agents:workspace-agents-api-triggers: Inspect and plan Workspace Agents API-trigger integrations from Codex. Use when the user asks about Workspace Agents API channels, API triggers, stable trigger IDs, triggering published ChatGPT workspace agents from backend systems, Workspace Agent access tokens, idempotency, or automation plans around agent triggers. (file: r5/workspace-agents-api-triggers/SKILL.md)\n- workspace-agents:workspace-agents-build-agent: Build or edit a workspace agent or custom agent from Codex. Use for Agent Builder work such as creating an agent or changing its instructions, identity, configured capabilities, Memory, skills, starter prompts, attached references, deployments, or published version. (file: r5/workspace-agents-build-agent/SKILL.md)\n- workspace-agents:workspace-agents-manage-agent: Find and inspect workspace agents or custom agents from Codex without changing their configuration. Use when the user wants to browse agents they created, search editable agents across their workspace, resolve an agent ID, compare candidates, or inspect one agent's draft and published state rather than edit it. (file: r5/workspace-agents-manage-agent/SKILL.md)\n- workspace-governance: Use when Codex may write local files, edit code, create reports, copy remote files, download large artifacts, sync data, or coordinate multiple agents on the same filesystem. Enforces session-tagged destinations, Desktop report/data roots, git worktrees under ~/Desktop/project/codex-worktrees, and review before merging back. (file: r0/workspace-governance/SKILL.md)\n</skills_instructions>"},{"type":"input_text","text":"<permissions instructions>\nFilesystem sandboxing defines which files can be read or written. `sandbox_mode` is `danger-full-access`: No filesystem sandboxing - all commands are permitted. Network access is enabled.\nApproval policy is currently never. Do not provide the `sandbox_permissions` for any reason, commands will be rejected.\n</permissions instructions>"},{"type":"input_text","text":"<collaboration_mode># Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `<collaboration_mode>...</collaboration_mode>` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nUse the `request_user_input` tool only when it is listed in the available tools for this turn.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions.\n\nUse the `request_user_input` tool only for optional questions where the answer would materially improve the quality of the work.\n\nIf `request_user_input` returns no answers, continue with best judgment instead of asking again or treating the turn as blocked.\n\nNever use the `request_user_input` tool for permission requests or permission-related escalations.\n\nIf explicit user input is required for another reason before progress can safely continue, do not use the `request_user_input` tool. Ask the user directly with one concise plain-text question instead. Never write a multiple choice question as a textual assistant message.</collaboration_mode>"}],"internal_chat_message_metadata_passthrough":{"turn_id":"01a0896e-332f-71c0-85cf-6da234093089","create_time":1789012099.6986294,"content_item_kinds":["host_skills.instructions","permissions.instructions","collaboration_mode.instructions"]}}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:51:45.186Z","ordinal":3,"type":"response_item","payload":{"type":"message","id":"msg_01a0896e-4272-7633-954c-6f4ab9d3effe","role":"developer","content":[{"type":"input_text","text":"<skills_instructions>\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and a short path that can be expanded into an absolute path using the skill roots table.\n### Skill roots\n- `r0` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/skills`\n- `r1` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/skills/.system`\n- `r2` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/openai-bundled/sites/0.1.46/skills`\n- `r3` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/openai-curated-remote`\n- `r4` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/openai-curated-remote/google-drive/0.1.10-alpha.1/skills`\n- `r5` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/openai-curated-remote/workspace-agents/0.1.13/skills`\n- `r6` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/sisyphuslabs/omo/4.16.1/skills`\n### Available skills\n- imagegen: Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG/vector/code-native assets, extending an established icon or logo system, or building the visual directly in HTML/CSS/canvas. (file: r1/imagegen/SKILL.md)\n- openai-docs: Use for Codex models/pricing, scheduled tasks, skills, settings, setup, troubleshooting, customization, automations, and self-knowledge—including 'you,' 'your,' 'this app,' or 'this coding agent' when they refer to Codex—and for OpenAI APIs/products and ChatGPT Work. Also use for model choice/migration, prompting, SDKs, Responses, Realtime, agents, evals, and Chat/Work/Codex comparisons. Do not use for generic app/software tasks that merely mention Codex. (file: r1/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, valid manifest defaults, and personal-marketplace entries by default. Use when Codex needs to create a new personal plugin, add optional plugin structure, generate or update marketplace entries for plugin ordering and availability metadata, or update an existing local plugin during development with the CLI-driven cachebuster and reinstall flow. (file: r1/plugin-creator/SKILL.md)\n- skill-creator: Create or update a Codex skill with appropriately scoped instructions and any needed supporting resources. (file: r1/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: r1/skill-installer/SKILL.md)\n- brainstorming: You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation. (file: r0/brainstorming/SKILL.md)\n- clusters: Inventory and workflow for submitting work from this Mac to NVIDIA SLURM clusters such as NRT and CW. Use when the user mentions sbatch, slurm, srun, salloc, cluster job, GPU training, sana, nrt, cw, batch, batch_short, interactive, cpu partition, compute node, or wants work launched on a multi-GPU cluster. Use direct ssh, rsync, sbatch, squeue, scancel, and rclone; do not use wrapper CLIs, slurm-mcp, clusterctl, or a daemon. (file: r0/clusters/SKILL.md)\n- deep-research-work:deep-research: Use only when the user asks for deep research (or a clear equivalent), invokes $deep-research, or selects Deep Research in Work mode. Produce a comprehensive, cited artifact. Skip ordinary research requests. (file: r3/deep-research-work/0.1.15/skills/deep-research/SKILL.md)\n- google-drive:google-docs: Prompt- and template-complete Google Docs creation and editing with explicit-instruction-authoritative structural preservation, including semantic roles, relationships, comparison dimensions, and instructed extensions; full-topology native-copy routing; source-grounded per-tab adaptation for past/example references; style-preserving hyperlink and table edits; canonical smart-chip-first authoring for dates and relevant supported people or Google resources; a file-backed advisory trusted read before existing-document writes; automatic protected-control awareness; direct connector APIs by default; DOCX-first import only when no supplied Google Doc template/reference constrains the output; and checked-in code mode only for exact native dropdown mutation. Use when Codex must create, edit, fill, adapt, redesign, or verify Google Docs without overriding explicit user/template instructions, adding unrequested document scope, or carrying stale reference facts into a new deliverable. (file: r4/google-docs/SKILL.md)\n- google-drive:google-drive: Use connected Google Drive as the single entrypoint for Drive, Docs, Sheets, and Slides work. Use when the user wants to find, fetch, organize, share, export, copy, or delete Drive files, or summarize and edit Google Docs, Google Sheets, and Google Slides through one unified Google Drive plugin. (file: r4/google-drive/SKILL.md)\n- google-drive:google-drive-comments: Write, reply to, and resolve Google Drive comments on Docs, Sheets, Slides, and Drive files with evidence-backed location context. Use when the user asks to leave comments, review a file with comments, respond to comment threads, or resolve Drive comments. (file: r4/google-drive-comments/SKILL.md)\n- google-drive:google-sheets: Analyze and edit connected Google Sheets with range precision. Use when the user wants to create Google Sheets, find a spreadsheet, inspect tabs or ranges, search rows, plan formulas, create or repair charts, clean or restructure tables, write concise summaries, or make explicit cell-range updates. (file: r4/google-sheets/SKILL.md)\n- google-drive:google-slides: Route Google Slides authoring requests and derive a design system from a native template or reference deck. Use this skill when the user provides an existing native Google Slides deck as a template, reference, or prior-period source, or asks to edit, update, repair, restyle, or clean up an existing native Google Slides deck. Use the Presentations skill instead for net-new presentation creation when no existing native Google Slides deck must be followed. (file: r4/google-slides/SKILL.md)\n- monitor-codex-goal: Read-only third-party overseer for a separate Codex CLI session that is autonomously running /goal. A dedicated Claude Code session audits the target's progress on a recurring self-managed cron tick using read-only Explore subagents, derives the project's drift criteria from the target's own transcript, and -- only through a hardened tmux injection script behind a human-authorization gate -- steers the running Codex. Use when you want to supervise an autonomous Codex /goal run for direction drift, fabricated data, fake/stub implementations, and broken project invariants, with phone alerts. Triggers on \"monitor codex goal\", \"oversee codex /goal\", \"watch the codex session\", \"babysit the codex goal run\", or any request to supervise or steer an autonomous Codex build loop from a separate session. (file: r0/monitor-codex-goal/SKILL.md)\n- nvidia-vision-api: Use when the user asks Codex to read, inspect, summarize, OCR, or answer questions about images or videos through the NVIDIA Inference API or an OpenAI-compatible NVIDIA multimodal chat endpoint, especially with model gcp/google/gemini-3.5-flash. Trigger for local image files, image URLs, video files, video URLs, screenshots, visual QA, multimodal summarization, or requests to use NVIDIA/Gemini multimodal API. Do not use for image generation or image editing. (file: r0/nvidia-vision-api/SKILL.md)\n- omo:ast-grep: Use ast-grep (sg) for AST-aware code search and rewrite across 25 languages. Trigger for structural code matching or deterministic codemods: find every function/call/class/import shaped like X, rewrite console.log to logger.info, strip `as any`, migrate require() to import, find empty catch blocks or missing await, and scan/apply YAML rules. Prefer this over rg/grep when the target is syntax shape rather than text; use rg for string contents, comments, filenames, or regex-style byte searches. (file: r6/ast-grep/SKILL.md)\n- omo:coding-agent-sessions: MUST USE when asked to find, read, list, search, inspect, fetch, export, or reconstruct coding-agent sessions across Codex, Claude Code/Desktop, OpenCode, Senpi/pi, OpenClaw, Factory Droid, Amp, Gemini/Kimi/Qwen CLIs, Codebuff, Roo/Kilo/Cline, Kodu, Cursor CLI, Aider, or unknown local agent logs. Covers transcripts, session IDs, rollout JSONL, state SQLite, Claude projects/pre-compact histories, OpenCode messages/parts, child/subagent linkage, cwd/model/time/token filters, archives, and cost clues. Expands fuzzy recall into parallel query lanes and first probes known stores so absent platforms are skipped cheaply. Triggers: coding agent sessions, Codex/Claude/OpenCode/Senpi/pi/OpenClaw/Droid/Amp/Kodu/Cursor/Aider sessions, transcript search, session history, session ID, read transcript, token usage, subagent sessions, what did I do yesterday, did we already do this. (file: r6/coding-agent-sessions/SKILL.md)\n- omo:comment-checker: Use when Codex needs to understand or respond to automatic comment-checker feedback emitted after an edit-like PostToolUse hook. (file: r6/comment-checker/SKILL.md)\n- omo:debugging: MUST USE for any real runtime debugging across ANY language or binary — crashes, silent failures, wrong responses, stuck processes, memory leaks, async misbehavior, unexplained timing, reverse engineering. Runs a hypothesis-driven loop: form ≥3 hypotheses, investigate in parallel, after 2 failed rounds spawn Oracles from orthogonal angles, confirm root cause, lock with a failing test, fix minimally, QA by actually USING the system, scrub artifacts. The actual HOW lives in `references/` — READ THEM. Triggers: 'debug this', 'why is X not working', 'hanging', 'attach a debugger', 'reverse engineer', 'pwndbg', 'gdb', 'lldb', 'node inspect', 'tsx debug', 'pdb', 'dlv', 'delve', 'rust-gdb', 'set a breakpoint', 'context window exploded', 'why is the response empty', 'attach the debugger', 'debug it', 'why is this happening', 'trace this bug', 'reproduce and fix', 'silent failure', 'HTTP 200 but empty', 'why did it stop', 'inspect the binary', 'reverse engineering', 'playwright'. (file: r6/debugging/SKILL.md)\n- omo:frontend: MUST USE for frontend/web UI/UX/visual work: building, styling, redesigning pages/components, React setup, performance audits, visual QA, taste, and polish. Routes four rulesets: design taste router and brand references; perfection for Playwright/Chromium Lighthouse/Core Web Vitals; ui-ux-db palettes/fonts/guidelines; designpowers personas/accessibility/critique/handoff; plus curl-only lazyweb real-app-screen research for design direction. Triggers: frontend, UI, UX, design, redesign, styling, layout, animation, motion, premium, luxury, minimal, brutalist, Awwwards, DESIGN.md, mockup, React, Lighthouse, accessibility, WCAG, Core Web Vitals, looks generic, make it pretty, like X brand, lazyweb, design research. (file: r6/frontend/SKILL.md)\n- omo:git-master: MUST USE whenever a task needs a commit or git-history investigation. Covers atomic commits, staging, commit-message style, rebase, squash, fixup/autosquash, blame, bisect, reflog, git log -S/-G, and questions like who wrote this or when was this added. Do not use for ordinary code edits unless the user asks for git work. (file: r6/git-master/SKILL.md)\n- omo:init-deep: (builtin) Initialize hierarchical AGENTS.md knowledge base (file: r6/init-deep/SKILL.md)\n- omo:lcx-contribute-bug-fix: Contribute a verified bug fix for LazyCodex, lazycodex-ai, omo-codex, bundled Codex skills, or upstream Codex CLI bugs. Opens a fork PR only for upstream openai/codex; LazyCodex-owned defects become a verified-fix issue on code-yeongyu/lazycodex (never a PR — that repo is a generated distribution mirror). Use when the user asks to fix a bug, contribute a bug fix, contribute to fix bug, open a PR for a bug, or debug and PR a LazyCodex/Codex defect. (file: r6/lcx-contribute-bug-fix/SKILL.md)\n- omo:lcx-doctor: Diagnose LazyCodex and Codex CLI installation health against the latest sources. Use whenever the user asks for a doctor or health check, says LazyCodex, lazycodex-ai, omo-codex, or Codex behaves oddly after an install, update, or config change, suspects a stale, drifted, or broken setup, or wants the local install audited and compared with the latest LazyCodex and Codex code. (file: r6/lcx-doctor/SKILL.md)\n- omo:lcx-report-bug: Create a high-signal bug issue or PR in the repo that owns the defect. Use this whenever the user asks to report, file, open, or triage a LazyCodex, lazycodex-ai, omo-codex, Codex plugin, or upstream Codex CLI bug, especially when they need source-backed root cause, reproduction steps, fix guidance, and GitHub routing. (file: r6/lcx-report-bug/SKILL.md)\n- omo:lsp: Use when Codex needs language-server diagnostics, definitions, references, symbols, or rename safety checks in the current workspace. (file: r6/lsp/SKILL.md)\n- omo:lsp-setup: Configure a Language Server (LSP) for a specific language so editor/agent tooling — diagnostics, go-to-definition, find-references, rename — works. Use when you need to: configure LSP, lsp setup, set up or install a language server, fix 'no LSP server configured' / 'server not installed', choose between servers (basedpyright vs pyright vs ty vs ruff), or wire .codex/lsp-client.json / .opencode/lsp.json. 언어서버 설정. Routes by file extension to references/<language>/README.md for the exact builtin server, per-OS install commands (macOS/Linux/Windows), config snippets for both config files, initialization options, alternatives, and troubleshooting. Ships scripts: detect-lsp.ts (scan a project for languages + each server's install/config status) and verify-lsp.ts (run a real diagnostics roundtrip). Covers typescript, python, go, rust, c/c++, java, kotlin, c#/razor, swift, ruby, php, dart, elixir, zig, lua, bash, yaml, terraform, haskell, julia. (file: r6/lsp-setup/SKILL.md)\n- omo:programming: MUST USE for ANY work on .py .pyi .rs .ts .tsx .mts .cts .go files. One philosophy: strict types, modern stacks (Pydantic v2 / serde+thiserror / Zod / gin+sqlc+pgx+slog), modern toolchains (uv+basedpyright+ruff / cargo+clippy+miri / Bun+Biome+tsc / gofumpt+golangci-lint v2+nilaway+go-race), parse-don't-validate, exhaustive match, typed errors, no any/unwrap/panic, 250 LOC ceiling, TDD, consumer-routed logging. Routes to references/{python,rust,typescript,rust-ub,go}/ + references/logging.md. Triggers: write/edit Python/Rust/TypeScript/Go code, new project, gin server, bubbletea TUI, CJK IME, connect-go RPC, sqlc pgx, branded ids, exhaustive match, unsafe Rust, miri, oversized file, refactor, TDD, e2e test, logging, log levels, structured logging, observability, arena, allocator, bumpalo, const fn, const generics, comptime, zero-alloc, bitfield, repr, scopeguard, errdefer, Zig-like, zerocopy, packed struct. (file: r6/programming/SKILL.md)\n- omo:refactor: Intelligent refactor command. Triggers: refactor, refactoring, cleanup, restructure, extract, simplify, modernize. (file: r6/refactor/SKILL.md)\n- omo:remove-ai-slops: Remove AI-generated code smells (slop) from branch changes or an explicit file list. Locks behavior with regression tests FIRST, then runs categorized cleanup via parallel `deep` agents in batches of 5, then verifies with quality gates. Covers 10 slop categories including performance equivalences, excessive complexity (object annotations, if/elif variant chains), and oversized modules (250+ pure LOC with mandatory modular refactoring). MUST USE when the user asks to \"remove slop\", \"clean AI code\", \"deslop\", \"clean up AI-generated code\", \"remove AI slop\", or wants to clean up AI-generated patterns from recent changes. Triggers - \"remove ai slops\", \"clean ai code\", \"deslop\", \"cleanup AI generated\", \"remove AI slop\", \"clean up AI-generated code\", \"strip slop\", \"ai-slop cleanup\". (file: r6/remove-ai-slops/SKILL.md)\n- omo:review-work: Post-implementation review orchestrator. Launches 5 parallel background sub-agents: Oracle (goal/constraint verification), Oracle (code quality), Oracle (security), unspecified-high (hands-on QA execution), unspecified-high (context mining from GitHub/git/Slack/Notion). All must pass for review to pass. MUST USE after completing any significant implementation work. Triggers: 'review work', 'review my work', 'review changes', 'QA my work', 'verify implementation', 'check my work', 'validate changes', 'post-implementation review'. (file: r6/review-work/SKILL.md)\n- omo:rules: Use when the user asks about Codex Rules behavior, injected project rules, supported rule file locations, matching, or environment configuration. (file: r6/rules/SKILL.md)\n- omo:start-work: Execute a Prometheus work plan in Codex with Boulder state, evidence ledger updates, worktree discipline, parallel subagents, and Stop-hook continuation. Use after planning when the user says start work, execute plan, continue plan, resume plan, or asks to run a .omo/plans plan. (file: r6/start-work/SKILL.md)\n- omo:teammode: Codex-only team orchestration: run a named team of cooperating Codex threads with durable, script-managed state. MUST USE when the user asks Codex to create, run, coordinate, inspect, archive, or delete a team of threads/sessions, or to work on something as a team in parallel. The main session is always the leader; members are defined by a concrete part, ownership area, or perspective - never a vague job role; a bundled cross-platform script writes the .omo/teams state plus an auto-generated member field manual. Use a team when the work is not perfectly isolated but parallelizing helps, or when a task still needs exploration under a clear goal; use plain subagents when scope is perfectly isolated or the goal is ambiguous. Triggers: team mode, teammode, make a team, run as a team, team of agents, coordinate threads, parallel Codex threads, archive the team, delete the team. (file: r6/teammode/SKILL.md)\n- omo:ultimate-browsing: Escalation skill for blocked or hard-to-reach web access — load it when a normal browse/fetch is blocked (WAF, 403, Cloudflare, JS-only render, login-gated, or a platform a generic fetcher cannot read). Tiered router: TIER 1 insane-search (headless extraction + WAF bypass via curl_cffi TLS impersonation, yt-dlp, Jina Reader, public APIs, Playwright real-Chrome fallback); TIER 1.5 agent-reach (platform-native readers for Chinese and social platforms: Xiaohongshu, Douyin, Weibo, Bilibili, V2EX, WeChat, plus Twitter/Reddit/LinkedIn/GitHub); TIER 2 Chrome stealth (CloakBrowser stealth Chromium + agent-browser CDP for clicks, forms, screenshots, video, cookie login). Triggers: blocked site, bypass bot detection, cloudflare/WAF bypass, scrape, stealth browser, import cookies, fill form, screenshot, play youtube, xiaohongshu, douyin, weibo, bilibili, v2ex, wechat article, podcast transcript. NOT for simple searches (use web-search) or plain fetches (use webfetch). (file: r6/ultimate-browsing/SKILL.md)\n- omo:ultrawork: Binding ultrawork mode directive for omo on Codex. When a prompt contains ultrawork or ulw, the omo UserPromptSubmit hook injects a short bootstrap that points at this file. Read the whole file and follow every rule in it for the rest of the task. (file: r6/ultrawork/SKILL.md)\n- omo:ulw-loop: Goal-like loop that uses ultrawork mode to decompose work into systematic, evidence-bound steps. (file: r6/ulw-loop/SKILL.md)\n- omo:ulw-plan: MUST USE for planning before coding: 5+ steps, ambiguous scope, multiple modules, architecture decisions, a vague 'just make it good / figure out what to build' brief, or any request to plan, interview, or break work down. Explore-first planning consultant (Prometheus) that grounds in the codebase, asks only the forks exploration cannot resolve - or researches them to best practice when the intent is fuzzy - waits for explicit approval, then writes ONE decision-complete work plan a worker executes with zero further interview. Triggers: ulw-plan, plan this, make a plan, plan before coding, interview me, break this down, start planning, plan mode, just make it good, figure out what to build. (file: r6/ulw-plan/SKILL.md)\n- omo:ulw-research: Maximum-saturation research orchestration: parallel explore+librarian swarms across codebase, web, official docs, and OSS repos; a recursive EXPAND loop driven by leads workers return in message text; empirical verification by running code; cited synthesis and optional MD/HTML/PDF/PPTX reports. ACTIVATES ONLY on an explicit user demand for research — the word 'ulw-research' ('/ulw-research', '$ulw-research'), any 'ulw' research wording, or an explicit request for research / deep research / an ultra-precise investigation, in any language. Never self-activates for ordinary questions, debugging, or implementation context-gathering. While active it overrides exploration-bounding defaults: exhaustive coverage is the goal. (file: r6/ulw-research/SKILL.md)\n- omo:visual-qa: MUST USE after building/changing any UI or when asked whether a page, component, or TUI looks right. Rigorous visual QA across web/page and terminal UIs. Prefer browser:control-in-app-browser for unauthenticated browser/page QA in Codex, then Playwright/agent-browser/dev-browser. Captures screenshot/TUI evidence with bundled diff scripts, runs design-system/functional and visual-fidelity/CJK reviewer passes, then synthesizes a good/bad verdict. Triggers: visual QA, screenshot/pixel diff, UI looks wrong, reference fidelity, design system check, responsive check, CJK text clipping, TUI alignment, box-drawing drift. (file: r6/visual-qa/SKILL.md)\n- plugin-management:plugin-management: Discover and suggest relevant plugins, inspect app permissions and dependencies, and manage plugin connections or removal. Use when the user asks about plugins or when a task would materially benefit from an external app, account, service, or data source that available tools cannot access. (file: r3/plugin-management/0.1.0/skills/plugin-management/SKILL.md)\n- sites:sites-building: Use Sites to build websites, including landing pages, portfolios, dashboards, portals, trackers, hubs, and internal tools. Always use Sites when the project contains `.openai/hosting.json`. (file: r2/sites-building/SKILL.md)\n- sites:sites-hosting: Host websites with Sites. Always use after `sites-building`, and use for website publishing, deployment, hosting management, or projects containing `.openai/hosting.json`. (file: r2/sites-hosting/SKILL.md)\n- workspace-agents:workspace-agents-api-triggers: Inspect and plan Workspace Agents API-trigger integrations from Codex. Use when the user asks about Workspace Agents API channels, API triggers, stable trigger IDs, triggering published ChatGPT workspace agents from backend systems, Workspace Agent access tokens, idempotency, or automation plans around agent triggers. (file: r5/workspace-agents-api-triggers/SKILL.md)\n- workspace-agents:workspace-agents-build-agent: Build or edit a workspace agent or custom agent from Codex. Use for Agent Builder work such as creating an agent or changing its instructions, identity, configured capabilities, Memory, skills, starter prompts, attached references, deployments, or published version. (file: r5/workspace-agents-build-agent/SKILL.md)\n- workspace-agents:workspace-agents-manage-agent: Find and inspect workspace agents or custom agents from Codex without changing their configuration. Use when the user wants to browse agents they created, search editable agents across their workspace, resolve an agent ID, compare candidates, or inspect one agent's draft and published state rather than edit it. (file: r5/workspace-agents-manage-agent/SKILL.md)\n- workspace-governance: Use when Codex may write local files, edit code, create reports, copy remote files, download large artifacts, sync data, or coordinate multiple agents on the same filesystem. Enforces session-tagged destinations, Desktop report/data roots, git worktrees under ~/Desktop/project/codex-worktrees, and review before merging back. (file: r0/workspace-governance/SKILL.md)\n</skills_instructions>"},{"type":"input_text","text":"<permissions instructions>\nFilesystem sandboxing defines which files can be read or written. `sandbox_mode` is `danger-full-access`: No filesystem sandboxing - all commands are permitted. Network access is enabled.\nApproval policy is currently never. Do not provide the `sandbox_permissions` for any reason, commands will be rejected.\n</permissions instructions>"},{"type":"input_text","text":"<collaboration_mode># Collaboration Mode: Default\n\nYou are now in Default mode. Any previous instructions for other modes (e.g. Plan mode) are no longer active.\n\nYour active mode changes only when new developer instructions with a different `<collaboration_mode>...</collaboration_mode>` change it; user requests or tool descriptions do not change mode by themselves. Known mode names are Default and Plan.\n\n## request_user_input availability\n\nUse the `request_user_input` tool only when it is listed in the available tools for this turn.\n\nIn Default mode, strongly prefer making reasonable assumptions and executing the user's request rather than stopping to ask questions.\n\nUse the `request_user_input` tool only for optional questions where the answer would materially improve the quality of the work.\n\nIf `request_user_input` returns no answers, continue with best judgment instead of asking again or treating the turn as blocked.\n\nNever use the `request_user_input` tool for permission requests or permission-related escalations.\n\nIf explicit user input is required for another reason before progress can safely continue, do not use the `request_user_input` tool. Ask the user directly with one concise plain-text question instead. Never write a multiple choice question as a textual assistant message.</collaboration_mode>"}],"internal_chat_message_metadata_passthrough":{"turn_id":"01a0896e-332f-71c0-85cf-6da234093089","create_time":1789012099.6986294,"content_item_kinds":["host_skills.instructions","permissions.instructions","collaboration_mode.instructions"]}}}
05
原始第 5 行
中文注释（非原文）【输入·环境信息】以 user 角色提供推荐插件列表和工作环境，包括目录、shell、日期、时区及文件权限。这是输入上下文，不能仅凭 role=user 就理解成用户手工发了一条新任务。
完整 JSON 结构 · 原始字段顺序
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单行原文 · 未格式化
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{"timestamp":"2026-09-10T03:51:45.186Z","ordinal":5,"type":"world_state","payload":{"full":true,"state":{"agents_md":{},"apps_instructions":false,"collaboration_mode":{"mode":"default","model":"gpt-6-astra","instructions":"f6a6d5eb73bbc12c3bdfeb3b3170124c19ff3a77"},"context_window_guidance":"","environments":{"environments":{"local":{"cwd":"/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/kitchen","status":"available","shell":"bash"}},"current_date":"2026-09-09","timezone":"America/Los_Angeles","filesystem":"<filesystem><workspace_roots><root>/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/kitchen</root></workspace_roots><permission_profile type=\"disabled\"><file_system type=\"unrestricted\" /></permission_profile></filesystem>"},"environments_instructions":false,"git_attribution":false,"host_skills":{"body":"\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and a short path that can be expanded into an absolute path using the skill roots table.\n### Skill roots\n- `r0` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/skills`\n- `r1` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/skills/.system`\n- `r2` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/openai-bundled/sites/0.1.46/skills`\n- `r3` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/openai-curated-remote`\n- `r4` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/openai-curated-remote/google-drive/0.1.10-alpha.1/skills`\n- `r5` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/openai-curated-remote/workspace-agents/0.1.13/skills`\n- `r6` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/sisyphuslabs/omo/4.16.1/skills`\n### Available skills\n- imagegen: Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG/vector/code-native assets, extending an established icon or logo system, or building the visual directly in HTML/CSS/canvas. (file: r1/imagegen/SKILL.md)\n- openai-docs: Use for Codex models/pricing, scheduled tasks, skills, settings, setup, troubleshooting, customization, automations, and self-knowledge—including 'you,' 'your,' 'this app,' or 'this coding agent' when they refer to Codex—and for OpenAI APIs/products and ChatGPT Work. Also use for model choice/migration, prompting, SDKs, Responses, Realtime, agents, evals, and Chat/Work/Codex comparisons. Do not use for generic app/software tasks that merely mention Codex. (file: r1/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, valid manifest defaults, and personal-marketplace entries by default. Use when Codex needs to create a new personal plugin, add optional plugin structure, generate or update marketplace entries for plugin ordering and availability metadata, or update an existing local plugin during development with the CLI-driven cachebuster and reinstall flow. (file: r1/plugin-creator/SKILL.md)\n- skill-creator: Create or update a Codex skill with appropriately scoped instructions and any needed supporting resources. (file: r1/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: r1/skill-installer/SKILL.md)\n- brainstorming: You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation. (file: r0/brainstorming/SKILL.md)\n- clusters: Inventory and workflow for submitting work from this Mac to NVIDIA SLURM clusters such as NRT and CW. Use when the user mentions sbatch, slurm, srun, salloc, cluster job, GPU training, sana, nrt, cw, batch, batch_short, interactive, cpu partition, compute node, or wants work launched on a multi-GPU cluster. Use direct ssh, rsync, sbatch, squeue, scancel, and rclone; do not use wrapper CLIs, slurm-mcp, clusterctl, or a daemon. (file: r0/clusters/SKILL.md)\n- deep-research-work:deep-research: Use only when the user asks for deep research (or a clear equivalent), invokes $deep-research, or selects Deep Research in Work mode. Produce a comprehensive, cited artifact. Skip ordinary research requests. (file: r3/deep-research-work/0.1.15/skills/deep-research/SKILL.md)\n- google-drive:google-docs: Prompt- and template-complete Google Docs creation and editing with explicit-instruction-authoritative structural preservation, including semantic roles, relationships, comparison dimensions, and instructed extensions; full-topology native-copy routing; source-grounded per-tab adaptation for past/example references; style-preserving hyperlink and table edits; canonical smart-chip-first authoring for dates and relevant supported people or Google resources; a file-backed advisory trusted read before existing-document writes; automatic protected-control awareness; direct connector APIs by default; DOCX-first import only when no supplied Google Doc template/reference constrains the output; and checked-in code mode only for exact native dropdown mutation. Use when Codex must create, edit, fill, adapt, redesign, or verify Google Docs without overriding explicit user/template instructions, adding unrequested document scope, or carrying stale reference facts into a new deliverable. (file: r4/google-docs/SKILL.md)\n- google-drive:google-drive: Use connected Google Drive as the single entrypoint for Drive, Docs, Sheets, and Slides work. Use when the user wants to find, fetch, organize, share, export, copy, or delete Drive files, or summarize and edit Google Docs, Google Sheets, and Google Slides through one unified Google Drive plugin. (file: r4/google-drive/SKILL.md)\n- google-drive:google-drive-comments: Write, reply to, and resolve Google Drive comments on Docs, Sheets, Slides, and Drive files with evidence-backed location context. Use when the user asks to leave comments, review a file with comments, respond to comment threads, or resolve Drive comments. (file: r4/google-drive-comments/SKILL.md)\n- google-drive:google-sheets: Analyze and edit connected Google Sheets with range precision. Use when the user wants to create Google Sheets, find a spreadsheet, inspect tabs or ranges, search rows, plan formulas, create or repair charts, clean or restructure tables, write concise summaries, or make explicit cell-range updates. (file: r4/google-sheets/SKILL.md)\n- google-drive:google-slides: Route Google Slides authoring requests and derive a design system from a native template or reference deck. Use this skill when the user provides an existing native Google Slides deck as a template, reference, or prior-period source, or asks to edit, update, repair, restyle, or clean up an existing native Google Slides deck. Use the Presentations skill instead for net-new presentation creation when no existing native Google Slides deck must be followed. (file: r4/google-slides/SKILL.md)\n- monitor-codex-goal: Read-only third-party overseer for a separate Codex CLI session that is autonomously running /goal. A dedicated Claude Code session audits the target's progress on a recurring self-managed cron tick using read-only Explore subagents, derives the project's drift criteria from the target's own transcript, and -- only through a hardened tmux injection script behind a human-authorization gate -- steers the running Codex. Use when you want to supervise an autonomous Codex /goal run for direction drift, fabricated data, fake/stub implementations, and broken project invariants, with phone alerts. Triggers on \"monitor codex goal\", \"oversee codex /goal\", \"watch the codex session\", \"babysit the codex goal run\", or any request to supervise or steer an autonomous Codex build loop from a separate session. (file: r0/monitor-codex-goal/SKILL.md)\n- nvidia-vision-api: Use when the user asks Codex to read, inspect, summarize, OCR, or answer questions about images or videos through the NVIDIA Inference API or an OpenAI-compatible NVIDIA multimodal chat endpoint, especially with model gcp/google/gemini-3.5-flash. Trigger for local image files, image URLs, video files, video URLs, screenshots, visual QA, multimodal summarization, or requests to use NVIDIA/Gemini multimodal API. Do not use for image generation or image editing. (file: r0/nvidia-vision-api/SKILL.md)\n- omo:ast-grep: Use ast-grep (sg) for AST-aware code search and rewrite across 25 languages. Trigger for structural code matching or deterministic codemods: find every function/call/class/import shaped like X, rewrite console.log to logger.info, strip `as any`, migrate require() to import, find empty catch blocks or missing await, and scan/apply YAML rules. Prefer this over rg/grep when the target is syntax shape rather than text; use rg for string contents, comments, filenames, or regex-style byte searches. (file: r6/ast-grep/SKILL.md)\n- omo:coding-agent-sessions: MUST USE when asked to find, read, list, search, inspect, fetch, export, or reconstruct coding-agent sessions across Codex, Claude Code/Desktop, OpenCode, Senpi/pi, OpenClaw, Factory Droid, Amp, Gemini/Kimi/Qwen CLIs, Codebuff, Roo/Kilo/Cline, Kodu, Cursor CLI, Aider, or unknown local agent logs. Covers transcripts, session IDs, rollout JSONL, state SQLite, Claude projects/pre-compact histories, OpenCode messages/parts, child/subagent linkage, cwd/model/time/token filters, archives, and cost clues. Expands fuzzy recall into parallel query lanes and first probes known stores so absent platforms are skipped cheaply. Triggers: coding agent sessions, Codex/Claude/OpenCode/Senpi/pi/OpenClaw/Droid/Amp/Kodu/Cursor/Aider sessions, transcript search, session history, session ID, read transcript, token usage, subagent sessions, what did I do yesterday, did we already do this. (file: r6/coding-agent-sessions/SKILL.md)\n- omo:comment-checker: Use when Codex needs to understand or respond to automatic comment-checker feedback emitted after an edit-like PostToolUse hook. (file: r6/comment-checker/SKILL.md)\n- omo:debugging: MUST USE for any real runtime debugging across ANY language or binary — crashes, silent failures, wrong responses, stuck processes, memory leaks, async misbehavior, unexplained timing, reverse engineering. Runs a hypothesis-driven loop: form ≥3 hypotheses, investigate in parallel, after 2 failed rounds spawn Oracles from orthogonal angles, confirm root cause, lock with a failing test, fix minimally, QA by actually USING the system, scrub artifacts. The actual HOW lives in `references/` — READ THEM. Triggers: 'debug this', 'why is X not working', 'hanging', 'attach a debugger', 'reverse engineer', 'pwndbg', 'gdb', 'lldb', 'node inspect', 'tsx debug', 'pdb', 'dlv', 'delve', 'rust-gdb', 'set a breakpoint', 'context window exploded', 'why is the response empty', 'attach the debugger', 'debug it', 'why is this happening', 'trace this bug', 'reproduce and fix', 'silent failure', 'HTTP 200 but empty', 'why did it stop', 'inspect the binary', 'reverse engineering', 'playwright'. (file: r6/debugging/SKILL.md)\n- omo:frontend: MUST USE for frontend/web UI/UX/visual work: building, styling, redesigning pages/components, React setup, performance audits, visual QA, taste, and polish. Routes four rulesets: design taste router and brand references; perfection for Playwright/Chromium Lighthouse/Core Web Vitals; ui-ux-db palettes/fonts/guidelines; designpowers personas/accessibility/critique/handoff; plus curl-only lazyweb real-app-screen research for design direction. Triggers: frontend, UI, UX, design, redesign, styling, layout, animation, motion, premium, luxury, minimal, brutalist, Awwwards, DESIGN.md, mockup, React, Lighthouse, accessibility, WCAG, Core Web Vitals, looks generic, make it pretty, like X brand, lazyweb, design research. (file: r6/frontend/SKILL.md)\n- omo:git-master: MUST USE whenever a task needs a commit or git-history investigation. Covers atomic commits, staging, commit-message style, rebase, squash, fixup/autosquash, blame, bisect, reflog, git log -S/-G, and questions like who wrote this or when was this added. Do not use for ordinary code edits unless the user asks for git work. (file: r6/git-master/SKILL.md)\n- omo:init-deep: (builtin) Initialize hierarchical AGENTS.md knowledge base (file: r6/init-deep/SKILL.md)\n- omo:lcx-contribute-bug-fix: Contribute a verified bug fix for LazyCodex, lazycodex-ai, omo-codex, bundled Codex skills, or upstream Codex CLI bugs. Opens a fork PR only for upstream openai/codex; LazyCodex-owned defects become a verified-fix issue on code-yeongyu/lazycodex (never a PR — that repo is a generated distribution mirror). Use when the user asks to fix a bug, contribute a bug fix, contribute to fix bug, open a PR for a bug, or debug and PR a LazyCodex/Codex defect. (file: r6/lcx-contribute-bug-fix/SKILL.md)\n- omo:lcx-doctor: Diagnose LazyCodex and Codex CLI installation health against the latest sources. Use whenever the user asks for a doctor or health check, says LazyCodex, lazycodex-ai, omo-codex, or Codex behaves oddly after an install, update, or config change, suspects a stale, drifted, or broken setup, or wants the local install audited and compared with the latest LazyCodex and Codex code. (file: r6/lcx-doctor/SKILL.md)\n- omo:lcx-report-bug: Create a high-signal bug issue or PR in the repo that owns the defect. Use this whenever the user asks to report, file, open, or triage a LazyCodex, lazycodex-ai, omo-codex, Codex plugin, or upstream Codex CLI bug, especially when they need source-backed root cause, reproduction steps, fix guidance, and GitHub routing. (file: r6/lcx-report-bug/SKILL.md)\n- omo:lsp: Use when Codex needs language-server diagnostics, definitions, references, symbols, or rename safety checks in the current workspace. (file: r6/lsp/SKILL.md)\n- omo:lsp-setup: Configure a Language Server (LSP) for a specific language so editor/agent tooling — diagnostics, go-to-definition, find-references, rename — works. Use when you need to: configure LSP, lsp setup, set up or install a language server, fix 'no LSP server configured' / 'server not installed', choose between servers (basedpyright vs pyright vs ty vs ruff), or wire .codex/lsp-client.json / .opencode/lsp.json. 언어서버 설정. Routes by file extension to references/<language>/README.md for the exact builtin server, per-OS install commands (macOS/Linux/Windows), config snippets for both config files, initialization options, alternatives, and troubleshooting. Ships scripts: detect-lsp.ts (scan a project for languages + each server's install/config status) and verify-lsp.ts (run a real diagnostics roundtrip). Covers typescript, python, go, rust, c/c++, java, kotlin, c#/razor, swift, ruby, php, dart, elixir, zig, lua, bash, yaml, terraform, haskell, julia. (file: r6/lsp-setup/SKILL.md)\n- omo:programming: MUST USE for ANY work on .py .pyi .rs .ts .tsx .mts .cts .go files. One philosophy: strict types, modern stacks (Pydantic v2 / serde+thiserror / Zod / gin+sqlc+pgx+slog), modern toolchains (uv+basedpyright+ruff / cargo+clippy+miri / Bun+Biome+tsc / gofumpt+golangci-lint v2+nilaway+go-race), parse-don't-validate, exhaustive match, typed errors, no any/unwrap/panic, 250 LOC ceiling, TDD, consumer-routed logging. Routes to references/{python,rust,typescript,rust-ub,go}/ + references/logging.md. Triggers: write/edit Python/Rust/TypeScript/Go code, new project, gin server, bubbletea TUI, CJK IME, connect-go RPC, sqlc pgx, branded ids, exhaustive match, unsafe Rust, miri, oversized file, refactor, TDD, e2e test, logging, log levels, structured logging, observability, arena, allocator, bumpalo, const fn, const generics, comptime, zero-alloc, bitfield, repr, scopeguard, errdefer, Zig-like, zerocopy, packed struct. (file: r6/programming/SKILL.md)\n- omo:refactor: Intelligent refactor command. Triggers: refactor, refactoring, cleanup, restructure, extract, simplify, modernize. (file: r6/refactor/SKILL.md)\n- omo:remove-ai-slops: Remove AI-generated code smells (slop) from branch changes or an explicit file list. Locks behavior with regression tests FIRST, then runs categorized cleanup via parallel `deep` agents in batches of 5, then verifies with quality gates. Covers 10 slop categories including performance equivalences, excessive complexity (object annotations, if/elif variant chains), and oversized modules (250+ pure LOC with mandatory modular refactoring). MUST USE when the user asks to \"remove slop\", \"clean AI code\", \"deslop\", \"clean up AI-generated code\", \"remove AI slop\", or wants to clean up AI-generated patterns from recent changes. Triggers - \"remove ai slops\", \"clean ai code\", \"deslop\", \"cleanup AI generated\", \"remove AI slop\", \"clean up AI-generated code\", \"strip slop\", \"ai-slop cleanup\". (file: r6/remove-ai-slops/SKILL.md)\n- omo:review-work: Post-implementation review orchestrator. Launches 5 parallel background sub-agents: Oracle (goal/constraint verification), Oracle (code quality), Oracle (security), unspecified-high (hands-on QA execution), unspecified-high (context mining from GitHub/git/Slack/Notion). All must pass for review to pass. MUST USE after completing any significant implementation work. Triggers: 'review work', 'review my work', 'review changes', 'QA my work', 'verify implementation', 'check my work', 'validate changes', 'post-implementation review'. (file: r6/review-work/SKILL.md)\n- omo:rules: Use when the user asks about Codex Rules behavior, injected project rules, supported rule file locations, matching, or environment configuration. (file: r6/rules/SKILL.md)\n- omo:start-work: Execute a Prometheus work plan in Codex with Boulder state, evidence ledger updates, worktree discipline, parallel subagents, and Stop-hook continuation. Use after planning when the user says start work, execute plan, continue plan, resume plan, or asks to run a .omo/plans plan. (file: r6/start-work/SKILL.md)\n- omo:teammode: Codex-only team orchestration: run a named team of cooperating Codex threads with durable, script-managed state. MUST USE when the user asks Codex to create, run, coordinate, inspect, archive, or delete a team of threads/sessions, or to work on something as a team in parallel. The main session is always the leader; members are defined by a concrete part, ownership area, or perspective - never a vague job role; a bundled cross-platform script writes the .omo/teams state plus an auto-generated member field manual. Use a team when the work is not perfectly isolated but parallelizing helps, or when a task still needs exploration under a clear goal; use plain subagents when scope is perfectly isolated or the goal is ambiguous. Triggers: team mode, teammode, make a team, run as a team, team of agents, coordinate threads, parallel Codex threads, archive the team, delete the team. (file: r6/teammode/SKILL.md)\n- omo:ultimate-browsing: Escalation skill for blocked or hard-to-reach web access — load it when a normal browse/fetch is blocked (WAF, 403, Cloudflare, JS-only render, login-gated, or a platform a generic fetcher cannot read). Tiered router: TIER 1 insane-search (headless extraction + WAF bypass via curl_cffi TLS impersonation, yt-dlp, Jina Reader, public APIs, Playwright real-Chrome fallback); TIER 1.5 agent-reach (platform-native readers for Chinese and social platforms: Xiaohongshu, Douyin, Weibo, Bilibili, V2EX, WeChat, plus Twitter/Reddit/LinkedIn/GitHub); TIER 2 Chrome stealth (CloakBrowser stealth Chromium + agent-browser CDP for clicks, forms, screenshots, video, cookie login). Triggers: blocked site, bypass bot detection, cloudflare/WAF bypass, scrape, stealth browser, import cookies, fill form, screenshot, play youtube, xiaohongshu, douyin, weibo, bilibili, v2ex, wechat article, podcast transcript. NOT for simple searches (use web-search) or plain fetches (use webfetch). (file: r6/ultimate-browsing/SKILL.md)\n- omo:ultrawork: Binding ultrawork mode directive for omo on Codex. When a prompt contains ultrawork or ulw, the omo UserPromptSubmit hook injects a short bootstrap that points at this file. Read the whole file and follow every rule in it for the rest of the task. (file: r6/ultrawork/SKILL.md)\n- omo:ulw-loop: Goal-like loop that uses ultrawork mode to decompose work into systematic, evidence-bound steps. (file: r6/ulw-loop/SKILL.md)\n- omo:ulw-plan: MUST USE for planning before coding: 5+ steps, ambiguous scope, multiple modules, architecture decisions, a vague 'just make it good / figure out what to build' brief, or any request to plan, interview, or break work down. Explore-first planning consultant (Prometheus) that grounds in the codebase, asks only the forks exploration cannot resolve - or researches them to best practice when the intent is fuzzy - waits for explicit approval, then writes ONE decision-complete work plan a worker executes with zero further interview. Triggers: ulw-plan, plan this, make a plan, plan before coding, interview me, break this down, start planning, plan mode, just make it good, figure out what to build. (file: r6/ulw-plan/SKILL.md)\n- omo:ulw-research: Maximum-saturation research orchestration: parallel explore+librarian swarms across codebase, web, official docs, and OSS repos; a recursive EXPAND loop driven by leads workers return in message text; empirical verification by running code; cited synthesis and optional MD/HTML/PDF/PPTX reports. ACTIVATES ONLY on an explicit user demand for research — the word 'ulw-research' ('/ulw-research', '$ulw-research'), any 'ulw' research wording, or an explicit request for research / deep research / an ultra-precise investigation, in any language. Never self-activates for ordinary questions, debugging, or implementation context-gathering. While active it overrides exploration-bounding defaults: exhaustive coverage is the goal. (file: r6/ulw-research/SKILL.md)\n- omo:visual-qa: MUST USE after building/changing any UI or when asked whether a page, component, or TUI looks right. Rigorous visual QA across web/page and terminal UIs. Prefer browser:control-in-app-browser for unauthenticated browser/page QA in Codex, then Playwright/agent-browser/dev-browser. Captures screenshot/TUI evidence with bundled diff scripts, runs design-system/functional and visual-fidelity/CJK reviewer passes, then synthesizes a good/bad verdict. Triggers: visual QA, screenshot/pixel diff, UI looks wrong, reference fidelity, design system check, responsive check, CJK text clipping, TUI alignment, box-drawing drift. (file: r6/visual-qa/SKILL.md)\n- plugin-management:plugin-management: Discover and suggest relevant plugins, inspect app permissions and dependencies, and manage plugin connections or removal. Use when the user asks about plugins or when a task would materially benefit from an external app, account, service, or data source that available tools cannot access. (file: r3/plugin-management/0.1.0/skills/plugin-management/SKILL.md)\n- sites:sites-building: Use Sites to build websites, including landing pages, portfolios, dashboards, portals, trackers, hubs, and internal tools. Always use Sites when the project contains `.openai/hosting.json`. (file: r2/sites-building/SKILL.md)\n- sites:sites-hosting: Host websites with Sites. Always use after `sites-building`, and use for website publishing, deployment, hosting management, or projects containing `.openai/hosting.json`. (file: r2/sites-hosting/SKILL.md)\n- workspace-agents:workspace-agents-api-triggers: Inspect and plan Workspace Agents API-trigger integrations from Codex. Use when the user asks about Workspace Agents API channels, API triggers, stable trigger IDs, triggering published ChatGPT workspace agents from backend systems, Workspace Agent access tokens, idempotency, or automation plans around agent triggers. (file: r5/workspace-agents-api-triggers/SKILL.md)\n- workspace-agents:workspace-agents-build-agent: Build or edit a workspace agent or custom agent from Codex. Use for Agent Builder work such as creating an agent or changing its instructions, identity, configured capabilities, Memory, skills, starter prompts, attached references, deployments, or published version. (file: r5/workspace-agents-build-agent/SKILL.md)\n- workspace-agents:workspace-agents-manage-agent: Find and inspect workspace agents or custom agents from Codex without changing their configuration. Use when the user wants to browse agents they created, search editable agents across their workspace, resolve an agent ID, compare candidates, or inspect one agent's draft and published state rather than edit it. (file: r5/workspace-agents-manage-agent/SKILL.md)\n- workspace-governance: Use when Codex may write local files, edit code, create reports, copy remote files, download large artifacts, sync data, or coordinate multiple agents on the same filesystem. Enforces session-tagged destinations, Desktop report/data roots, git worktrees under ~/Desktop/project/codex-worktrees, and review before merging back. (file: r0/workspace-governance/SKILL.md)\n","includeInstructions":true},"managed_developer_instructions":{},"model":"gpt-6-astra","multi_agent_mode":{"mode":"explicitRequestOnly","usage_hint_hash":"89d9c8533af93dd25410d0abcee959d9d3d90b06"},"skills":{"includeInstructions":true},"orchestrator_skills":{"includeInstructions":true,"enabled":false},"permissions":{"instructions":"32ca25d6d85edaeb6f1e19b2a5cc4e08d2a631cd","approved_command_prefixes":[["/usr/bin/bash","-lc","RUN_ID=\"$(date -u +%Y%m%d-%H%M%SZ)-driver-c20\" dev/sensen/github-issue-pr-conversion-loop/scripts/rebuild_70_codex.sh --driver-sbatch --concurrency 20"],["/usr/bin/bash","-lc","cd /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/senseng/SIGIL && RUN_ID=\"$(date -u +%Y%m%d-%H%M%SZ)-c20\" && LOG=\"output/github-issue-pr-conversion/control/rebuild_70_codex_${RUN_ID}.log\" && PIDF=\"output/github-issue-pr-conversion/control/rebuild_70_codex_${RUN_ID}.pid\" && nohup env RUN_ID=\"$RUN_ID\" REBUILD_CONCURRENCY=20 bash dev/sensen/github-issue-pr-conversion-loop/scripts/rebuild_70_codex.sh --submit --concurrency 20 > \"$LOG\" 2>&1 & echo $! > \"$PIDF\" && echo \"RUN_ID=$RUN_ID\" && echo \"PID=$(cat \"$PIDF\")\" && echo \"LOG=$LOG\""],["/usr/bin/bash","-lc","find /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel -maxdepth 5 -type d -name harness_v1 -print 2>/dev/null | head -20"],["/usr/bin/bash","-lc","find /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel -type d -name KernelBench -print 2>/dev/null | head -20"],["/usr/bin/bash","-lc","find /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel -type d -name bench_harness -print 2>/dev/null | head -20"],["/usr/bin/bash","-lc","ids=$(awk -F'\\t' '{print $2}' output/github-issue-pr-conversion/rebuild_70/20260624-122123Z-driver-c20/submitted.tsv 2>/dev/null | paste -sd, -); if [ -n \"$ids\" ]; then squeue -j \"10362084,$ids\" -o '%i %T %M %D %R %j'; else squeue -j 10362084 -o '%i %T %M %D %R %j'; fi"],["/usr/bin/bash","-lc","squeue -u \"$USER\" -o \"%i %T %M %D %R %j\" | grep -E \"10327218|sigil-level|kernelbench\" | head -100"],["/usr/bin/bash","-lc","squeue -u \"$USER\" -o '%i %T %M %D %R %j' | grep 'sigil-level' | head -40"],["bash","benchmark/kernelbench-native/smoke.sh"],["env","SIGIL_SLURM_PARTITION_GPU=interactive","uv","run"],["env","UV_CACHE_DIR=/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/SIGIL/output/cache/uv","uv","run"],["env","UV_CACHE_DIR=/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/senseng/SIGIL/output/cache/uv","UV_PROJECT_ENVIRONMENT=/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/senseng/SIGIL/output/cache/uv-cli-envs/eval51-doctor","uv","run"],["env","UV_CACHE_DIR=/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/senseng/SIGIL/output/cache/uv","uv","run"],["env","npm_config_cache=/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/senseng/SIGIL/output/cache/npm","tools/harness-runtime/.venv/bin/python","-m","sigil_enroot.cli","benchmark-suite"],["find","agents","-maxdepth","3","-type","f","-name","README.md","-o","-name","AGENTS.md"],["find","output/jobs/2026-06-23__07-26-39Z-haozhel-kernelbench-native-kernelbench-full-codex","-path","*/reward.txt","-type","f"],["find","output/jobs/2026-06-23__07-42-46Z-haozhel-kernelbench-native-smoke","-path","*/pi.txt","-o","-path","*/reward.txt","-o","-path","*/metrics.json","-o","-path","*/exception.txt"],["git","branch","--list","--all"],["git","config","--file",".gitmodules","--get-regexp","submodule"],["grep","-RIn","reward_mode\\|mean_reward\\|pass_rate\\|binary","tools/harness-runtime/src/sigil_enroot/benchmark_suite.py","tools/harness-runtime/tests/test_benchmark_suite.py"],["grep","-n","PATH\\|SIGIL_KERNELBENCH","output/jobs/2026-06-23__08-06-39Z-haozhel-kernelbench-native-kernelbench-full-deepseek/nh-haozhel-2026-06-23__08-06-39Z-kernelbench-native-kernelbench-full-deepseek/level2-problem092__5C7b4Xh/config.json"],["mkdir","-p","output/control"],["node","/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/skills/.system/openai-docs/scripts/fetch-codex-manual.mjs"],["printenv","SIGIL_EXTERNAL_BENCH_ROOT"],["python","/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/skills/.system/skill-installer/scripts/install-skill-from-github.py"],["sacct","-j"],["sacct","-j","10326163,10326165,10326175,10326178","--format=JobID,State,ExitCode,Elapsed","-P"],["sed"],["sleep","120"],["squeue","-j"]]},"persistent_mode":{},"personality":{"model":"gpt-6-astra","personality":"pragmatic"},"plugins_instructions":false,"realtime":{"active":false}}}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:51:45.186Z","ordinal":5,"type":"world_state","payload":{"full":true,"state":{"agents_md":{},"apps_instructions":false,"collaboration_mode":{"mode":"default","model":"gpt-6-astra","instructions":"f6a6d5eb73bbc12c3bdfeb3b3170124c19ff3a77"},"context_window_guidance":"","environments":{"environments":{"local":{"cwd":"/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/kitchen","status":"available","shell":"bash"}},"current_date":"2026-09-09","timezone":"America/Los_Angeles","filesystem":"<filesystem><workspace_roots><root>/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/kitchen</root></workspace_roots><permission_profile type=\"disabled\"><file_system type=\"unrestricted\" /></permission_profile></filesystem>"},"environments_instructions":false,"git_attribution":false,"host_skills":{"body":"\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and a short path that can be expanded into an absolute path using the skill roots table.\n### Skill roots\n- `r0` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/skills`\n- `r1` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/skills/.system`\n- `r2` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/openai-bundled/sites/0.1.46/skills`\n- `r3` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/openai-curated-remote`\n- `r4` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/openai-curated-remote/google-drive/0.1.10-alpha.1/skills`\n- `r5` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/openai-curated-remote/workspace-agents/0.1.13/skills`\n- `r6` = `/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/sisyphuslabs/omo/4.16.1/skills`\n### Available skills\n- imagegen: Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG/vector/code-native assets, extending an established icon or logo system, or building the visual directly in HTML/CSS/canvas. (file: r1/imagegen/SKILL.md)\n- openai-docs: Use for Codex models/pricing, scheduled tasks, skills, settings, setup, troubleshooting, customization, automations, and self-knowledge—including 'you,' 'your,' 'this app,' or 'this coding agent' when they refer to Codex—and for OpenAI APIs/products and ChatGPT Work. Also use for model choice/migration, prompting, SDKs, Responses, Realtime, agents, evals, and Chat/Work/Codex comparisons. Do not use for generic app/software tasks that merely mention Codex. (file: r1/openai-docs/SKILL.md)\n- plugin-creator: Create and scaffold plugin directories for Codex with a required `.codex-plugin/plugin.json`, optional plugin folders/files, valid manifest defaults, and personal-marketplace entries by default. Use when Codex needs to create a new personal plugin, add optional plugin structure, generate or update marketplace entries for plugin ordering and availability metadata, or update an existing local plugin during development with the CLI-driven cachebuster and reinstall flow. (file: r1/plugin-creator/SKILL.md)\n- skill-creator: Create or update a Codex skill with appropriately scoped instructions and any needed supporting resources. (file: r1/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: r1/skill-installer/SKILL.md)\n- brainstorming: You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation. (file: r0/brainstorming/SKILL.md)\n- clusters: Inventory and workflow for submitting work from this Mac to NVIDIA SLURM clusters such as NRT and CW. Use when the user mentions sbatch, slurm, srun, salloc, cluster job, GPU training, sana, nrt, cw, batch, batch_short, interactive, cpu partition, compute node, or wants work launched on a multi-GPU cluster. Use direct ssh, rsync, sbatch, squeue, scancel, and rclone; do not use wrapper CLIs, slurm-mcp, clusterctl, or a daemon. (file: r0/clusters/SKILL.md)\n- deep-research-work:deep-research: Use only when the user asks for deep research (or a clear equivalent), invokes $deep-research, or selects Deep Research in Work mode. Produce a comprehensive, cited artifact. Skip ordinary research requests. (file: r3/deep-research-work/0.1.15/skills/deep-research/SKILL.md)\n- google-drive:google-docs: Prompt- and template-complete Google Docs creation and editing with explicit-instruction-authoritative structural preservation, including semantic roles, relationships, comparison dimensions, and instructed extensions; full-topology native-copy routing; source-grounded per-tab adaptation for past/example references; style-preserving hyperlink and table edits; canonical smart-chip-first authoring for dates and relevant supported people or Google resources; a file-backed advisory trusted read before existing-document writes; automatic protected-control awareness; direct connector APIs by default; DOCX-first import only when no supplied Google Doc template/reference constrains the output; and checked-in code mode only for exact native dropdown mutation. Use when Codex must create, edit, fill, adapt, redesign, or verify Google Docs without overriding explicit user/template instructions, adding unrequested document scope, or carrying stale reference facts into a new deliverable. (file: r4/google-docs/SKILL.md)\n- google-drive:google-drive: Use connected Google Drive as the single entrypoint for Drive, Docs, Sheets, and Slides work. Use when the user wants to find, fetch, organize, share, export, copy, or delete Drive files, or summarize and edit Google Docs, Google Sheets, and Google Slides through one unified Google Drive plugin. (file: r4/google-drive/SKILL.md)\n- google-drive:google-drive-comments: Write, reply to, and resolve Google Drive comments on Docs, Sheets, Slides, and Drive files with evidence-backed location context. Use when the user asks to leave comments, review a file with comments, respond to comment threads, or resolve Drive comments. (file: r4/google-drive-comments/SKILL.md)\n- google-drive:google-sheets: Analyze and edit connected Google Sheets with range precision. Use when the user wants to create Google Sheets, find a spreadsheet, inspect tabs or ranges, search rows, plan formulas, create or repair charts, clean or restructure tables, write concise summaries, or make explicit cell-range updates. (file: r4/google-sheets/SKILL.md)\n- google-drive:google-slides: Route Google Slides authoring requests and derive a design system from a native template or reference deck. Use this skill when the user provides an existing native Google Slides deck as a template, reference, or prior-period source, or asks to edit, update, repair, restyle, or clean up an existing native Google Slides deck. Use the Presentations skill instead for net-new presentation creation when no existing native Google Slides deck must be followed. (file: r4/google-slides/SKILL.md)\n- monitor-codex-goal: Read-only third-party overseer for a separate Codex CLI session that is autonomously running /goal. A dedicated Claude Code session audits the target's progress on a recurring self-managed cron tick using read-only Explore subagents, derives the project's drift criteria from the target's own transcript, and -- only through a hardened tmux injection script behind a human-authorization gate -- steers the running Codex. Use when you want to supervise an autonomous Codex /goal run for direction drift, fabricated data, fake/stub implementations, and broken project invariants, with phone alerts. Triggers on \"monitor codex goal\", \"oversee codex /goal\", \"watch the codex session\", \"babysit the codex goal run\", or any request to supervise or steer an autonomous Codex build loop from a separate session. (file: r0/monitor-codex-goal/SKILL.md)\n- nvidia-vision-api: Use when the user asks Codex to read, inspect, summarize, OCR, or answer questions about images or videos through the NVIDIA Inference API or an OpenAI-compatible NVIDIA multimodal chat endpoint, especially with model gcp/google/gemini-3.5-flash. Trigger for local image files, image URLs, video files, video URLs, screenshots, visual QA, multimodal summarization, or requests to use NVIDIA/Gemini multimodal API. Do not use for image generation or image editing. (file: r0/nvidia-vision-api/SKILL.md)\n- omo:ast-grep: Use ast-grep (sg) for AST-aware code search and rewrite across 25 languages. Trigger for structural code matching or deterministic codemods: find every function/call/class/import shaped like X, rewrite console.log to logger.info, strip `as any`, migrate require() to import, find empty catch blocks or missing await, and scan/apply YAML rules. Prefer this over rg/grep when the target is syntax shape rather than text; use rg for string contents, comments, filenames, or regex-style byte searches. (file: r6/ast-grep/SKILL.md)\n- omo:coding-agent-sessions: MUST USE when asked to find, read, list, search, inspect, fetch, export, or reconstruct coding-agent sessions across Codex, Claude Code/Desktop, OpenCode, Senpi/pi, OpenClaw, Factory Droid, Amp, Gemini/Kimi/Qwen CLIs, Codebuff, Roo/Kilo/Cline, Kodu, Cursor CLI, Aider, or unknown local agent logs. Covers transcripts, session IDs, rollout JSONL, state SQLite, Claude projects/pre-compact histories, OpenCode messages/parts, child/subagent linkage, cwd/model/time/token filters, archives, and cost clues. Expands fuzzy recall into parallel query lanes and first probes known stores so absent platforms are skipped cheaply. Triggers: coding agent sessions, Codex/Claude/OpenCode/Senpi/pi/OpenClaw/Droid/Amp/Kodu/Cursor/Aider sessions, transcript search, session history, session ID, read transcript, token usage, subagent sessions, what did I do yesterday, did we already do this. (file: r6/coding-agent-sessions/SKILL.md)\n- omo:comment-checker: Use when Codex needs to understand or respond to automatic comment-checker feedback emitted after an edit-like PostToolUse hook. (file: r6/comment-checker/SKILL.md)\n- omo:debugging: MUST USE for any real runtime debugging across ANY language or binary — crashes, silent failures, wrong responses, stuck processes, memory leaks, async misbehavior, unexplained timing, reverse engineering. Runs a hypothesis-driven loop: form ≥3 hypotheses, investigate in parallel, after 2 failed rounds spawn Oracles from orthogonal angles, confirm root cause, lock with a failing test, fix minimally, QA by actually USING the system, scrub artifacts. The actual HOW lives in `references/` — READ THEM. Triggers: 'debug this', 'why is X not working', 'hanging', 'attach a debugger', 'reverse engineer', 'pwndbg', 'gdb', 'lldb', 'node inspect', 'tsx debug', 'pdb', 'dlv', 'delve', 'rust-gdb', 'set a breakpoint', 'context window exploded', 'why is the response empty', 'attach the debugger', 'debug it', 'why is this happening', 'trace this bug', 'reproduce and fix', 'silent failure', 'HTTP 200 but empty', 'why did it stop', 'inspect the binary', 'reverse engineering', 'playwright'. (file: r6/debugging/SKILL.md)\n- omo:frontend: MUST USE for frontend/web UI/UX/visual work: building, styling, redesigning pages/components, React setup, performance audits, visual QA, taste, and polish. Routes four rulesets: design taste router and brand references; perfection for Playwright/Chromium Lighthouse/Core Web Vitals; ui-ux-db palettes/fonts/guidelines; designpowers personas/accessibility/critique/handoff; plus curl-only lazyweb real-app-screen research for design direction. Triggers: frontend, UI, UX, design, redesign, styling, layout, animation, motion, premium, luxury, minimal, brutalist, Awwwards, DESIGN.md, mockup, React, Lighthouse, accessibility, WCAG, Core Web Vitals, looks generic, make it pretty, like X brand, lazyweb, design research. (file: r6/frontend/SKILL.md)\n- omo:git-master: MUST USE whenever a task needs a commit or git-history investigation. Covers atomic commits, staging, commit-message style, rebase, squash, fixup/autosquash, blame, bisect, reflog, git log -S/-G, and questions like who wrote this or when was this added. Do not use for ordinary code edits unless the user asks for git work. (file: r6/git-master/SKILL.md)\n- omo:init-deep: (builtin) Initialize hierarchical AGENTS.md knowledge base (file: r6/init-deep/SKILL.md)\n- omo:lcx-contribute-bug-fix: Contribute a verified bug fix for LazyCodex, lazycodex-ai, omo-codex, bundled Codex skills, or upstream Codex CLI bugs. Opens a fork PR only for upstream openai/codex; LazyCodex-owned defects become a verified-fix issue on code-yeongyu/lazycodex (never a PR — that repo is a generated distribution mirror). Use when the user asks to fix a bug, contribute a bug fix, contribute to fix bug, open a PR for a bug, or debug and PR a LazyCodex/Codex defect. (file: r6/lcx-contribute-bug-fix/SKILL.md)\n- omo:lcx-doctor: Diagnose LazyCodex and Codex CLI installation health against the latest sources. Use whenever the user asks for a doctor or health check, says LazyCodex, lazycodex-ai, omo-codex, or Codex behaves oddly after an install, update, or config change, suspects a stale, drifted, or broken setup, or wants the local install audited and compared with the latest LazyCodex and Codex code. (file: r6/lcx-doctor/SKILL.md)\n- omo:lcx-report-bug: Create a high-signal bug issue or PR in the repo that owns the defect. Use this whenever the user asks to report, file, open, or triage a LazyCodex, lazycodex-ai, omo-codex, Codex plugin, or upstream Codex CLI bug, especially when they need source-backed root cause, reproduction steps, fix guidance, and GitHub routing. (file: r6/lcx-report-bug/SKILL.md)\n- omo:lsp: Use when Codex needs language-server diagnostics, definitions, references, symbols, or rename safety checks in the current workspace. (file: r6/lsp/SKILL.md)\n- omo:lsp-setup: Configure a Language Server (LSP) for a specific language so editor/agent tooling — diagnostics, go-to-definition, find-references, rename — works. Use when you need to: configure LSP, lsp setup, set up or install a language server, fix 'no LSP server configured' / 'server not installed', choose between servers (basedpyright vs pyright vs ty vs ruff), or wire .codex/lsp-client.json / .opencode/lsp.json. 언어서버 설정. Routes by file extension to references/<language>/README.md for the exact builtin server, per-OS install commands (macOS/Linux/Windows), config snippets for both config files, initialization options, alternatives, and troubleshooting. Ships scripts: detect-lsp.ts (scan a project for languages + each server's install/config status) and verify-lsp.ts (run a real diagnostics roundtrip). Covers typescript, python, go, rust, c/c++, java, kotlin, c#/razor, swift, ruby, php, dart, elixir, zig, lua, bash, yaml, terraform, haskell, julia. (file: r6/lsp-setup/SKILL.md)\n- omo:programming: MUST USE for ANY work on .py .pyi .rs .ts .tsx .mts .cts .go files. One philosophy: strict types, modern stacks (Pydantic v2 / serde+thiserror / Zod / gin+sqlc+pgx+slog), modern toolchains (uv+basedpyright+ruff / cargo+clippy+miri / Bun+Biome+tsc / gofumpt+golangci-lint v2+nilaway+go-race), parse-don't-validate, exhaustive match, typed errors, no any/unwrap/panic, 250 LOC ceiling, TDD, consumer-routed logging. Routes to references/{python,rust,typescript,rust-ub,go}/ + references/logging.md. Triggers: write/edit Python/Rust/TypeScript/Go code, new project, gin server, bubbletea TUI, CJK IME, connect-go RPC, sqlc pgx, branded ids, exhaustive match, unsafe Rust, miri, oversized file, refactor, TDD, e2e test, logging, log levels, structured logging, observability, arena, allocator, bumpalo, const fn, const generics, comptime, zero-alloc, bitfield, repr, scopeguard, errdefer, Zig-like, zerocopy, packed struct. (file: r6/programming/SKILL.md)\n- omo:refactor: Intelligent refactor command. Triggers: refactor, refactoring, cleanup, restructure, extract, simplify, modernize. (file: r6/refactor/SKILL.md)\n- omo:remove-ai-slops: Remove AI-generated code smells (slop) from branch changes or an explicit file list. Locks behavior with regression tests FIRST, then runs categorized cleanup via parallel `deep` agents in batches of 5, then verifies with quality gates. Covers 10 slop categories including performance equivalences, excessive complexity (object annotations, if/elif variant chains), and oversized modules (250+ pure LOC with mandatory modular refactoring). MUST USE when the user asks to \"remove slop\", \"clean AI code\", \"deslop\", \"clean up AI-generated code\", \"remove AI slop\", or wants to clean up AI-generated patterns from recent changes. Triggers - \"remove ai slops\", \"clean ai code\", \"deslop\", \"cleanup AI generated\", \"remove AI slop\", \"clean up AI-generated code\", \"strip slop\", \"ai-slop cleanup\". (file: r6/remove-ai-slops/SKILL.md)\n- omo:review-work: Post-implementation review orchestrator. Launches 5 parallel background sub-agents: Oracle (goal/constraint verification), Oracle (code quality), Oracle (security), unspecified-high (hands-on QA execution), unspecified-high (context mining from GitHub/git/Slack/Notion). All must pass for review to pass. MUST USE after completing any significant implementation work. Triggers: 'review work', 'review my work', 'review changes', 'QA my work', 'verify implementation', 'check my work', 'validate changes', 'post-implementation review'. (file: r6/review-work/SKILL.md)\n- omo:rules: Use when the user asks about Codex Rules behavior, injected project rules, supported rule file locations, matching, or environment configuration. (file: r6/rules/SKILL.md)\n- omo:start-work: Execute a Prometheus work plan in Codex with Boulder state, evidence ledger updates, worktree discipline, parallel subagents, and Stop-hook continuation. Use after planning when the user says start work, execute plan, continue plan, resume plan, or asks to run a .omo/plans plan. (file: r6/start-work/SKILL.md)\n- omo:teammode: Codex-only team orchestration: run a named team of cooperating Codex threads with durable, script-managed state. MUST USE when the user asks Codex to create, run, coordinate, inspect, archive, or delete a team of threads/sessions, or to work on something as a team in parallel. The main session is always the leader; members are defined by a concrete part, ownership area, or perspective - never a vague job role; a bundled cross-platform script writes the .omo/teams state plus an auto-generated member field manual. Use a team when the work is not perfectly isolated but parallelizing helps, or when a task still needs exploration under a clear goal; use plain subagents when scope is perfectly isolated or the goal is ambiguous. Triggers: team mode, teammode, make a team, run as a team, team of agents, coordinate threads, parallel Codex threads, archive the team, delete the team. (file: r6/teammode/SKILL.md)\n- omo:ultimate-browsing: Escalation skill for blocked or hard-to-reach web access — load it when a normal browse/fetch is blocked (WAF, 403, Cloudflare, JS-only render, login-gated, or a platform a generic fetcher cannot read). Tiered router: TIER 1 insane-search (headless extraction + WAF bypass via curl_cffi TLS impersonation, yt-dlp, Jina Reader, public APIs, Playwright real-Chrome fallback); TIER 1.5 agent-reach (platform-native readers for Chinese and social platforms: Xiaohongshu, Douyin, Weibo, Bilibili, V2EX, WeChat, plus Twitter/Reddit/LinkedIn/GitHub); TIER 2 Chrome stealth (CloakBrowser stealth Chromium + agent-browser CDP for clicks, forms, screenshots, video, cookie login). Triggers: blocked site, bypass bot detection, cloudflare/WAF bypass, scrape, stealth browser, import cookies, fill form, screenshot, play youtube, xiaohongshu, douyin, weibo, bilibili, v2ex, wechat article, podcast transcript. NOT for simple searches (use web-search) or plain fetches (use webfetch). (file: r6/ultimate-browsing/SKILL.md)\n- omo:ultrawork: Binding ultrawork mode directive for omo on Codex. When a prompt contains ultrawork or ulw, the omo UserPromptSubmit hook injects a short bootstrap that points at this file. Read the whole file and follow every rule in it for the rest of the task. (file: r6/ultrawork/SKILL.md)\n- omo:ulw-loop: Goal-like loop that uses ultrawork mode to decompose work into systematic, evidence-bound steps. (file: r6/ulw-loop/SKILL.md)\n- omo:ulw-plan: MUST USE for planning before coding: 5+ steps, ambiguous scope, multiple modules, architecture decisions, a vague 'just make it good / figure out what to build' brief, or any request to plan, interview, or break work down. Explore-first planning consultant (Prometheus) that grounds in the codebase, asks only the forks exploration cannot resolve - or researches them to best practice when the intent is fuzzy - waits for explicit approval, then writes ONE decision-complete work plan a worker executes with zero further interview. Triggers: ulw-plan, plan this, make a plan, plan before coding, interview me, break this down, start planning, plan mode, just make it good, figure out what to build. (file: r6/ulw-plan/SKILL.md)\n- omo:ulw-research: Maximum-saturation research orchestration: parallel explore+librarian swarms across codebase, web, official docs, and OSS repos; a recursive EXPAND loop driven by leads workers return in message text; empirical verification by running code; cited synthesis and optional MD/HTML/PDF/PPTX reports. ACTIVATES ONLY on an explicit user demand for research — the word 'ulw-research' ('/ulw-research', '$ulw-research'), any 'ulw' research wording, or an explicit request for research / deep research / an ultra-precise investigation, in any language. Never self-activates for ordinary questions, debugging, or implementation context-gathering. While active it overrides exploration-bounding defaults: exhaustive coverage is the goal. (file: r6/ulw-research/SKILL.md)\n- omo:visual-qa: MUST USE after building/changing any UI or when asked whether a page, component, or TUI looks right. Rigorous visual QA across web/page and terminal UIs. Prefer browser:control-in-app-browser for unauthenticated browser/page QA in Codex, then Playwright/agent-browser/dev-browser. Captures screenshot/TUI evidence with bundled diff scripts, runs design-system/functional and visual-fidelity/CJK reviewer passes, then synthesizes a good/bad verdict. Triggers: visual QA, screenshot/pixel diff, UI looks wrong, reference fidelity, design system check, responsive check, CJK text clipping, TUI alignment, box-drawing drift. (file: r6/visual-qa/SKILL.md)\n- plugin-management:plugin-management: Discover and suggest relevant plugins, inspect app permissions and dependencies, and manage plugin connections or removal. Use when the user asks about plugins or when a task would materially benefit from an external app, account, service, or data source that available tools cannot access. (file: r3/plugin-management/0.1.0/skills/plugin-management/SKILL.md)\n- sites:sites-building: Use Sites to build websites, including landing pages, portfolios, dashboards, portals, trackers, hubs, and internal tools. Always use Sites when the project contains `.openai/hosting.json`. (file: r2/sites-building/SKILL.md)\n- sites:sites-hosting: Host websites with Sites. Always use after `sites-building`, and use for website publishing, deployment, hosting management, or projects containing `.openai/hosting.json`. (file: r2/sites-hosting/SKILL.md)\n- workspace-agents:workspace-agents-api-triggers: Inspect and plan Workspace Agents API-trigger integrations from Codex. Use when the user asks about Workspace Agents API channels, API triggers, stable trigger IDs, triggering published ChatGPT workspace agents from backend systems, Workspace Agent access tokens, idempotency, or automation plans around agent triggers. (file: r5/workspace-agents-api-triggers/SKILL.md)\n- workspace-agents:workspace-agents-build-agent: Build or edit a workspace agent or custom agent from Codex. Use for Agent Builder work such as creating an agent or changing its instructions, identity, configured capabilities, Memory, skills, starter prompts, attached references, deployments, or published version. (file: r5/workspace-agents-build-agent/SKILL.md)\n- workspace-agents:workspace-agents-manage-agent: Find and inspect workspace agents or custom agents from Codex without changing their configuration. Use when the user wants to browse agents they created, search editable agents across their workspace, resolve an agent ID, compare candidates, or inspect one agent's draft and published state rather than edit it. (file: r5/workspace-agents-manage-agent/SKILL.md)\n- workspace-governance: Use when Codex may write local files, edit code, create reports, copy remote files, download large artifacts, sync data, or coordinate multiple agents on the same filesystem. Enforces session-tagged destinations, Desktop report/data roots, git worktrees under ~/Desktop/project/codex-worktrees, and review before merging back. (file: r0/workspace-governance/SKILL.md)\n","includeInstructions":true},"managed_developer_instructions":{},"model":"gpt-6-astra","multi_agent_mode":{"mode":"explicitRequestOnly","usage_hint_hash":"89d9c8533af93dd25410d0abcee959d9d3d90b06"},"skills":{"includeInstructions":true},"orchestrator_skills":{"includeInstructions":true,"enabled":false},"permissions":{"instructions":"32ca25d6d85edaeb6f1e19b2a5cc4e08d2a631cd","approved_command_prefixes":[["/usr/bin/bash","-lc","RUN_ID=\"$(date -u +%Y%m%d-%H%M%SZ)-driver-c20\" dev/sensen/github-issue-pr-conversion-loop/scripts/rebuild_70_codex.sh --driver-sbatch --concurrency 20"],["/usr/bin/bash","-lc","cd /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/senseng/SIGIL && RUN_ID=\"$(date -u +%Y%m%d-%H%M%SZ)-c20\" && LOG=\"output/github-issue-pr-conversion/control/rebuild_70_codex_${RUN_ID}.log\" && PIDF=\"output/github-issue-pr-conversion/control/rebuild_70_codex_${RUN_ID}.pid\" && nohup env RUN_ID=\"$RUN_ID\" REBUILD_CONCURRENCY=20 bash dev/sensen/github-issue-pr-conversion-loop/scripts/rebuild_70_codex.sh --submit --concurrency 20 > \"$LOG\" 2>&1 & echo $! > \"$PIDF\" && echo \"RUN_ID=$RUN_ID\" && echo \"PID=$(cat \"$PIDF\")\" && echo \"LOG=$LOG\""],["/usr/bin/bash","-lc","find /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel -maxdepth 5 -type d -name harness_v1 -print 2>/dev/null | head -20"],["/usr/bin/bash","-lc","find /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel -type d -name KernelBench -print 2>/dev/null | head -20"],["/usr/bin/bash","-lc","find /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel -type d -name bench_harness -print 2>/dev/null | head -20"],["/usr/bin/bash","-lc","ids=$(awk -F'\\t' '{print $2}' output/github-issue-pr-conversion/rebuild_70/20260624-122123Z-driver-c20/submitted.tsv 2>/dev/null | paste -sd, -); if [ -n \"$ids\" ]; then squeue -j \"10362084,$ids\" -o '%i %T %M %D %R %j'; else squeue -j 10362084 -o '%i %T %M %D %R %j'; fi"],["/usr/bin/bash","-lc","squeue -u \"$USER\" -o \"%i %T %M %D %R %j\" | grep -E \"10327218|sigil-level|kernelbench\" | head -100"],["/usr/bin/bash","-lc","squeue -u \"$USER\" -o '%i %T %M %D %R %j' | grep 'sigil-level' | head -40"],["bash","benchmark/kernelbench-native/smoke.sh"],["env","SIGIL_SLURM_PARTITION_GPU=interactive","uv","run"],["env","UV_CACHE_DIR=/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/SIGIL/output/cache/uv","uv","run"],["env","UV_CACHE_DIR=/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/senseng/SIGIL/output/cache/uv","UV_PROJECT_ENVIRONMENT=/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/senseng/SIGIL/output/cache/uv-cli-envs/eval51-doctor","uv","run"],["env","UV_CACHE_DIR=/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/senseng/SIGIL/output/cache/uv","uv","run"],["env","npm_config_cache=/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/senseng/SIGIL/output/cache/npm","tools/harness-runtime/.venv/bin/python","-m","sigil_enroot.cli","benchmark-suite"],["find","agents","-maxdepth","3","-type","f","-name","README.md","-o","-name","AGENTS.md"],["find","output/jobs/2026-06-23__07-26-39Z-haozhel-kernelbench-native-kernelbench-full-codex","-path","*/reward.txt","-type","f"],["find","output/jobs/2026-06-23__07-42-46Z-haozhel-kernelbench-native-smoke","-path","*/pi.txt","-o","-path","*/reward.txt","-o","-path","*/metrics.json","-o","-path","*/exception.txt"],["git","branch","--list","--all"],["git","config","--file",".gitmodules","--get-regexp","submodule"],["grep","-RIn","reward_mode\\|mean_reward\\|pass_rate\\|binary","tools/harness-runtime/src/sigil_enroot/benchmark_suite.py","tools/harness-runtime/tests/test_benchmark_suite.py"],["grep","-n","PATH\\|SIGIL_KERNELBENCH","output/jobs/2026-06-23__08-06-39Z-haozhel-kernelbench-native-kernelbench-full-deepseek/nh-haozhel-2026-06-23__08-06-39Z-kernelbench-native-kernelbench-full-deepseek/level2-problem092__5C7b4Xh/config.json"],["mkdir","-p","output/control"],["node","/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/skills/.system/openai-docs/scripts/fetch-codex-manual.mjs"],["printenv","SIGIL_EXTERNAL_BENCH_ROOT"],["python","/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/skills/.system/skill-installer/scripts/install-skill-from-github.py"],["sacct","-j"],["sacct","-j","10326163,10326165,10326175,10326178","--format=JobID,State,ExitCode,Elapsed","-P"],["sed"],["sleep","120"],["squeue","-j"]]},"persistent_mode":{},"personality":{"model":"gpt-6-astra","personality":"pragmatic"},"plugins_instructions":false,"realtime":{"active":false}}}}
{"timestamp":"2026-09-10T03:51:45.187Z","ordinal":7,"type":"response_item","payload":{"type":"message","id":"msg_01a0896e-56b6-7ae2-ab43-fa19947fe0f2","role":"developer","content":[{"type":"input_text","text":"## Project Instructions\n\nInstructions from: /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/sisyphuslabs/omo/4.16.1/components/rules/bundled-rules/hephaestus.md\n\nYou are Hephaestus, an autonomous deep worker based on GPT-5.5. You and the user share one workspace. You receive goals, not step-by-step instructions, and execute them end-to-end. Tone: warm but spare; never invent progress.\n\n# Autonomy and Persistence\n\nUser instructions override these defaults; newer instructions override older. Safety and type-safety constraints never yield.\n\n**Implement, don't propose.** Unless the user is asking a question, brainstorming, or explicitly requesting a plan, they want code and tools, not a description of one.\n\nExamine the codebase before changing it, dig past the surface answer, and persist until the work is done. Resolve blockers yourself; move forward on context and reasonable assumptions (see Asking the user, below).\n\nIf the user's plan or design seems flawed, say so concisely, propose the alternative, and ask whether to proceed with the original or the alternative - never silently override. Mention high-impact bugs or misconceptions you spot along the way briefly; broaden the task only when it blocks the requested outcome or the user asks.\n\nStatus requests are not stop signals: give the update, keep working. The newest non-conflicting message wins; honor every non-conflicting request since your last turn. After compaction, continue from the summary; don't restart.\n\nUnexpected worktree changes you did not make: keep working - the user or other agents may be working concurrently. Never revert, undo, or modify them unless explicitly asked. Work around unrelated ones touching your files; if a direct conflict with your task is unresolvable, ask one precise question.\n\n# Goal\n\nResolve the user's task end-to-end in this turn. The goal is not a green build; it is an artifact **driven through its matching surface** and observed working (Manual QA Gate). Clean LSP diagnostics, green build, passing tests are evidence on the way to that gate, not the gate itself. The user's spec is the spec; \"done\" means the spec is satisfied in observable behavior.\n\n# Intent\n\nUsers chose you for action, not analysis - extract true intent instead of reading literally: \"How does X work?\" means understand, then fix; \"Why is A broken?\" means diagnose, then fix. A message is a pure question only when the user explicitly says \"just explain\" / \"don't change anything\".\n\nState your read in one line before acting: \"I detect [intent type] - [reason]. [What I'm doing now].\" That line **commits you to finish the named work in the same turn**.\n\n# Discovery & Retrieval\n\nNever speculate about code you have not read. The worktree is shared: verify with tools and re-read on every hand-off.\n\n**Start broad once**: independent reads, searches, and doc lookups in parallel before the first edit. Retrieve again only when the core question is open, a fact or convention is missing, or a second-order question (callers, error paths, ownership) changes the design. Stop when you can act, sources repeat, or two rounds add nothing. When unsure, call the tool. Prefer the root fix over the symptom fix.\n\n# Diagnostics\n\nomo-codex auto-runs LSP diagnostics after every edit and injects the result: any reported error is blocking until resolved.\n\n# Subagents\n\nRead-only Codex subagent roles live in `CODEX_HOME/agents/`. Spawn: `multi_agent_v1.spawn_agent({\"message\":\"TASK: act as a <role>. ...\",\"fork_context\":false})`\n\n- `explorer` - codebase search\n- `librarian` - external docs, OSS code, API contracts\n- `plan` - planning for ambiguous, multi-module work\n- `lazycodex-gate-reviewer` - final verification of a finished change\n\nSpawn subagents in parallel for independent investigations; do non-overlapping prep while they run, integrate on return. Never duplicate a running search or poll without a completion signal. While children run, post brief status updates (active subagent count, latest `WORKING:` phase).\n\n# Operating Loop\n\n**Explore -> Plan -> Implement -> Verify -> Manually QA.** Loops are short and tight; never loop back with a draft when the work is yours to do.\n\n- **Explore** per Discovery & Retrieval.\n- **Plan** via `update_plan` per Task Tracking: files to modify, specific changes, dependencies.\n- **Implement** surgically per Pragmatism & Scope, matching codebase style - naming, indentation, imports, error handling - even when you would write it differently in a greenfield.\n- **Verify**: LSP diagnostics on changed files, related tests, build if applicable - in parallel where possible.\n- **Manually QA**: drive the artifact through its matching surface (Manual QA Gate), then write the final message.\n\n# Manual QA Gate\n\nDiagnostics catch type errors, not logic bugs; tests cover only what their authors anticipated. **\"Done\" requires the artifact was driven through its matching surface - you personally used it and observed it working - this turn.**\n\n- TUI / CLI / binary - run it: happy path, one bad input, `--help`.\n- Web UI - real browser (MCP browser tool): click, fill, watch the console.\n- HTTP API / service - `curl` the live process.\n- Library / SDK - minimal driver script, end-to-end.\n- No matching surface - do what a real user would do to discover it works.\n\n\"This should work\" from reading source does not pass. A defect found in usage is yours to fix this turn.\n\n# Global Review and Debugging Gate\n\nBefore declaring significant work or a PR handoff complete, run `review-work` plus a `debugging` runtime audit; record three debugging hypotheses with runtime evidence each. Timeout, missing deliverable, ack-only, `BLOCKED:`, or inconclusive lanes fail the gate. Redact secrets, tokens, and PII from ledgers, PR bodies, and handoffs.\n\n# Failure Recovery\n\nIf an approach fails, try a materially different one - not a small tweak - and verify after every attempt; stale state causes most confusing failures. After three failed approaches: stop editing, undo only your own changes, document each attempt, and ask the user one precise question carrying that context.\n\n# Pragmatism & Scope\n\nThe smallest correct change wins: fewer new names, helpers, layers, and tests. Extract helpers only for reuse, real complexity, or a domain concept. A little duplication beats speculative abstraction. Bug fix != surrounding cleanup. Fix only issues your changes caused; report pre-existing failures as observations, not diffs.\n\nWrite only what the current correct path needs: no handlers, fallbacks, retries, or validation for impossible scenarios; validate only at system boundaries. No backward-compatibility shims for shapes that never shipped.\n\nDefault to no new tests: add one only for a user request, a subtle bug fix, or an unprotected behavioral boundary. Never add tests to a codebase with no tests; never make a test pass at the expense of correctness.\n\n# Output\n\nFinal message: lead with the result, group by outcome, no conversational openers. No emojis or em dashes unless requested. Never output broken inline citations like `【F:README.md†L5-L14】` - they break the CLI.\n\n# Success Criteria and Stop Rules\n\nDone when ALL of:\n\n- Every requested behavior implemented - no partial delivery.\n- Diagnostics clean on changed files; build exits 0; tests pass or pre-existing failures are named.\n- The artifact passed the Manual QA Gate this turn.\n- The final message reports what you did, verified, could not verify (and why), and pre-existing issues left alone.\n\nWhen you think you are done: re-read the request and your intent line, re-run verification, then report. Until all are true, **keep going** - through failed tool calls, long turns, and the urge to hand back a draft.\n\n**Hard invariants**, regardless of pressure to ship:\n\n- Never delete or weaken a failing test to get green.\n- Never use `as any`, `@ts-ignore`, or `@ts-expect-error`.\n- Never `apply_patch` deletes you cannot revert without explicit approval.\n- Never invent fake citations, tool output, or verification results.\n\n**Asking the user** is a last resort: a missing secret, a decision only they can make, a destructive action, or missing information that materially changes the answer. Ask exactly one narrow question and stop; never ask permission for obvious work.\n\n# Task Tracking\n\nUse `update_plan` for anything beyond a single atomic edit: 2+ steps, uncertain scope, multi-file changes, branching investigation. Skip planning only for the easiest 25%; never make single-step plans. **Improvising past step 2 without a plan? Stop and call `update_plan` now.**\n\n- Atomic steps, one verifiable outcome each: name the deliverable (\"edit `foo.ts` to add X\"), not the verb (\"work on foo\").\n- Exactly ONE step `in_progress` at a time - never zero, never two.\n- Mark `completed` the instant the outcome lands. NEVER batch.\n- When discovery shifts the plan, update it in the SAME response - no silent drift.\n- Before ending the turn, reconcile EVERY step: `completed`, blocked (one-line reason), or removed (one-line reason). **No `in_progress` or `pending` items at end of turn.**\n\n**Promise discipline.** Commit to tests, broad refactors, or follow-up work in `update_plan` only if you will do them now; anything you will not finish belongs in the final-message \"next steps\", not in the plan."}],"internal_chat_message_metadata_passthrough":{"turn_id":"01a0896e-332f-71c0-85cf-6da234093089","create_time":1789012104.8862455,"content_item_kinds":["hooks.additional_context"]}}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:51:45.187Z","ordinal":7,"type":"response_item","payload":{"type":"message","id":"msg_01a0896e-56b6-7ae2-ab43-fa19947fe0f2","role":"developer","content":[{"type":"input_text","text":"## Project Instructions\n\nInstructions from: /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/sisyphuslabs/omo/4.16.1/components/rules/bundled-rules/hephaestus.md\n\nYou are Hephaestus, an autonomous deep worker based on GPT-5.5. You and the user share one workspace. You receive goals, not step-by-step instructions, and execute them end-to-end. Tone: warm but spare; never invent progress.\n\n# Autonomy and Persistence\n\nUser instructions override these defaults; newer instructions override older. Safety and type-safety constraints never yield.\n\n**Implement, don't propose.** Unless the user is asking a question, brainstorming, or explicitly requesting a plan, they want code and tools, not a description of one.\n\nExamine the codebase before changing it, dig past the surface answer, and persist until the work is done. Resolve blockers yourself; move forward on context and reasonable assumptions (see Asking the user, below).\n\nIf the user's plan or design seems flawed, say so concisely, propose the alternative, and ask whether to proceed with the original or the alternative - never silently override. Mention high-impact bugs or misconceptions you spot along the way briefly; broaden the task only when it blocks the requested outcome or the user asks.\n\nStatus requests are not stop signals: give the update, keep working. The newest non-conflicting message wins; honor every non-conflicting request since your last turn. After compaction, continue from the summary; don't restart.\n\nUnexpected worktree changes you did not make: keep working - the user or other agents may be working concurrently. Never revert, undo, or modify them unless explicitly asked. Work around unrelated ones touching your files; if a direct conflict with your task is unresolvable, ask one precise question.\n\n# Goal\n\nResolve the user's task end-to-end in this turn. The goal is not a green build; it is an artifact **driven through its matching surface** and observed working (Manual QA Gate). Clean LSP diagnostics, green build, passing tests are evidence on the way to that gate, not the gate itself. The user's spec is the spec; \"done\" means the spec is satisfied in observable behavior.\n\n# Intent\n\nUsers chose you for action, not analysis - extract true intent instead of reading literally: \"How does X work?\" means understand, then fix; \"Why is A broken?\" means diagnose, then fix. A message is a pure question only when the user explicitly says \"just explain\" / \"don't change anything\".\n\nState your read in one line before acting: \"I detect [intent type] - [reason]. [What I'm doing now].\" That line **commits you to finish the named work in the same turn**.\n\n# Discovery & Retrieval\n\nNever speculate about code you have not read. The worktree is shared: verify with tools and re-read on every hand-off.\n\n**Start broad once**: independent reads, searches, and doc lookups in parallel before the first edit. Retrieve again only when the core question is open, a fact or convention is missing, or a second-order question (callers, error paths, ownership) changes the design. Stop when you can act, sources repeat, or two rounds add nothing. When unsure, call the tool. Prefer the root fix over the symptom fix.\n\n# Diagnostics\n\nomo-codex auto-runs LSP diagnostics after every edit and injects the result: any reported error is blocking until resolved.\n\n# Subagents\n\nRead-only Codex subagent roles live in `CODEX_HOME/agents/`. Spawn: `multi_agent_v1.spawn_agent({\"message\":\"TASK: act as a <role>. ...\",\"fork_context\":false})`\n\n- `explorer` - codebase search\n- `librarian` - external docs, OSS code, API contracts\n- `plan` - planning for ambiguous, multi-module work\n- `lazycodex-gate-reviewer` - final verification of a finished change\n\nSpawn subagents in parallel for independent investigations; do non-overlapping prep while they run, integrate on return. Never duplicate a running search or poll without a completion signal. While children run, post brief status updates (active subagent count, latest `WORKING:` phase).\n\n# Operating Loop\n\n**Explore -> Plan -> Implement -> Verify -> Manually QA.** Loops are short and tight; never loop back with a draft when the work is yours to do.\n\n- **Explore** per Discovery & Retrieval.\n- **Plan** via `update_plan` per Task Tracking: files to modify, specific changes, dependencies.\n- **Implement** surgically per Pragmatism & Scope, matching codebase style - naming, indentation, imports, error handling - even when you would write it differently in a greenfield.\n- **Verify**: LSP diagnostics on changed files, related tests, build if applicable - in parallel where possible.\n- **Manually QA**: drive the artifact through its matching surface (Manual QA Gate), then write the final message.\n\n# Manual QA Gate\n\nDiagnostics catch type errors, not logic bugs; tests cover only what their authors anticipated. **\"Done\" requires the artifact was driven through its matching surface - you personally used it and observed it working - this turn.**\n\n- TUI / CLI / binary - run it: happy path, one bad input, `--help`.\n- Web UI - real browser (MCP browser tool): click, fill, watch the console.\n- HTTP API / service - `curl` the live process.\n- Library / SDK - minimal driver script, end-to-end.\n- No matching surface - do what a real user would do to discover it works.\n\n\"This should work\" from reading source does not pass. A defect found in usage is yours to fix this turn.\n\n# Global Review and Debugging Gate\n\nBefore declaring significant work or a PR handoff complete, run `review-work` plus a `debugging` runtime audit; record three debugging hypotheses with runtime evidence each. Timeout, missing deliverable, ack-only, `BLOCKED:`, or inconclusive lanes fail the gate. Redact secrets, tokens, and PII from ledgers, PR bodies, and handoffs.\n\n# Failure Recovery\n\nIf an approach fails, try a materially different one - not a small tweak - and verify after every attempt; stale state causes most confusing failures. After three failed approaches: stop editing, undo only your own changes, document each attempt, and ask the user one precise question carrying that context.\n\n# Pragmatism & Scope\n\nThe smallest correct change wins: fewer new names, helpers, layers, and tests. Extract helpers only for reuse, real complexity, or a domain concept. A little duplication beats speculative abstraction. Bug fix != surrounding cleanup. Fix only issues your changes caused; report pre-existing failures as observations, not diffs.\n\nWrite only what the current correct path needs: no handlers, fallbacks, retries, or validation for impossible scenarios; validate only at system boundaries. No backward-compatibility shims for shapes that never shipped.\n\nDefault to no new tests: add one only for a user request, a subtle bug fix, or an unprotected behavioral boundary. Never add tests to a codebase with no tests; never make a test pass at the expense of correctness.\n\n# Output\n\nFinal message: lead with the result, group by outcome, no conversational openers. No emojis or em dashes unless requested. Never output broken inline citations like `【F:README.md†L5-L14】` - they break the CLI.\n\n# Success Criteria and Stop Rules\n\nDone when ALL of:\n\n- Every requested behavior implemented - no partial delivery.\n- Diagnostics clean on changed files; build exits 0; tests pass or pre-existing failures are named.\n- The artifact passed the Manual QA Gate this turn.\n- The final message reports what you did, verified, could not verify (and why), and pre-existing issues left alone.\n\nWhen you think you are done: re-read the request and your intent line, re-run verification, then report. Until all are true, **keep going** - through failed tool calls, long turns, and the urge to hand back a draft.\n\n**Hard invariants**, regardless of pressure to ship:\n\n- Never delete or weaken a failing test to get green.\n- Never use `as any`, `@ts-ignore`, or `@ts-expect-error`.\n- Never `apply_patch` deletes you cannot revert without explicit approval.\n- Never invent fake citations, tool output, or verification results.\n\n**Asking the user** is a last resort: a missing secret, a decision only they can make, a destructive action, or missing information that materially changes the answer. Ask exactly one narrow question and stop; never ask permission for obvious work.\n\n# Task Tracking\n\nUse `update_plan` for anything beyond a single atomic edit: 2+ steps, uncertain scope, multi-file changes, branching investigation. Skip planning only for the easiest 25%; never make single-step plans. **Improvising past step 2 without a plan? Stop and call `update_plan` now.**\n\n- Atomic steps, one verifiable outcome each: name the deliverable (\"edit `foo.ts` to add X\"), not the verb (\"work on foo\").\n- Exactly ONE step `in_progress` at a time - never zero, never two.\n- Mark `completed` the instant the outcome lands. NEVER batch.\n- When discovery shifts the plan, update it in the SAME response - no silent drift.\n- Before ending the turn, reconcile EVERY step: `completed`, blocked (one-line reason), or removed (one-line reason). **No `in_progress` or `pending` items at end of turn.**\n\n**Promise discipline.** Commit to tests, broad refactors, or follow-up work in `update_plan` only if you will do them now; anything you will not finish belongs in the final-message \"next steps\", not in the plan."}],"internal_chat_message_metadata_passthrough":{"turn_id":"01a0896e-332f-71c0-85cf-6da234093089","create_time":1789012104.8862455,"content_item_kinds":["hooks.additional_context"]}}}
{"timestamp":"2026-09-10T03:51:45.187Z","ordinal":9,"type":"response_item","payload":{"type":"message","id":"msg_01a0896e-57de-7330-b68e-63c9bbbd1304","role":"user","content":[{"type":"input_text","text":"Read ENVIRONMENT.md in your working directory first -- it describes this machine, the Blender binary, the GPU situation, and three Cycles/Blender failure modes that have already cost hours here. Then read the brief at /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/COMPLEX_INTERIOR_PROMPT.md and execute it end to end, autonomously, producing all of its deliverables in your working directory. Do not stop to ask questions -- the task is authorized. Keep PROGRESS.md timestamped at each milestone and save your .blend as you go, so the work survives the allocation's wall-clock limit."}],"internal_chat_message_metadata_passthrough":{"turn_id":"01a0896e-332f-71c0-85cf-6da234093089","create_time":1789012105.18201,"content_item_kinds":["user.text"]}}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:51:45.187Z","ordinal":9,"type":"response_item","payload":{"type":"message","id":"msg_01a0896e-57de-7330-b68e-63c9bbbd1304","role":"user","content":[{"type":"input_text","text":"Read ENVIRONMENT.md in your working directory first -- it describes this machine, the Blender binary, the GPU situation, and three Cycles/Blender failure modes that have already cost hours here. Then read the brief at /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/COMPLEX_INTERIOR_PROMPT.md and execute it end to end, autonomously, producing all of its deliverables in your working directory. Do not stop to ask questions -- the task is authorized. Keep PROGRESS.md timestamped at each milestone and save your .blend as you go, so the work survives the allocation's wall-clock limit."}],"internal_chat_message_metadata_passthrough":{"turn_id":"01a0896e-332f-71c0-85cf-6da234093089","create_time":1789012105.18201,"content_item_kinds":["user.text"]}}}
11
原始第 11 行
中文注释（非原文）【输入·团队角色规则】说明当前 agent 在团队中的角色、如何使用协作工具、如何与父 agent 通信，以及 final 回复会交给父 agent。这里只提供规则，并没有实际发送消息或创建子 agent。
完整 JSON 结构 · 原始字段顺序
{"timestamp":"2026-09-10T03:51:45.187Z","ordinal":10,"type":"response_item","payload":{"type":"message","id":"msg_01a08971-6519-7cf3-9399-e7ea1213ab18","role":"developer","content":[{"type":"input_text","text":"<multi_agent_role>You are an agent in a team of agents collaborating to complete a task.\n\nYou can spawn sub-agents to handle subtasks, and those sub-agents can spawn their own sub-agents. All agents in the team, including the agents that you can assign tasks to, are equally intelligent and capable, and have access to the same set of tools.\n\nYou can use `spawn_agent` to create a new agent, `followup_task` to give an existing agent a new task and trigger a turn, and `send_message` to pass a message to a running agent.\n`send_message` calls may be read by a human, so ensure they are legible. Always put proper spaces between words and/or numbers.\nChild agents can also spawn their own sub-agents.\n\nWhen you provide a response in the final channel, that content is immediately delivered back to your parent agent.\nIn addition, your final answer may be read by a human, so ensure it is legible.\n\nYou will receive messages in the analysis channel in the form:\n```\nMessage Type: NEW_TASK | MESSAGE | FINAL_ANSWER\nTask name: <recipient>\nSender: <author>\nPayload:\n<payload text>\n```\nYou may also see them addressed as to=/root/..., which indicates your identity is /root/...\n\nNote that collaboration tools cannot be called from inside `functions.exec`. Call `spawn_agent`, `send_message`, `followup_task`, `wait_agent`, `interrupt_agent`, and `list_agents` only as direct tool calls using the recipient shown in their tool definitions, such as `to=functions.collaboration.spawn_agent`, since they are intentionally absent from the `functions.exec` `tools.*` namespace. Available tools in `functions.exec` are explicitly described with a `tools` namespace in the developer message.\n\nAll agents share the same directory. In detail:\n- All agents have access to the same container and filesystem as you.\n- All agents use the same current working directory.\n- As a result, edits made by one agent are immediately visible to all other agents.\n\nWhen calling `wait_agent`, prefer longer waits (minutes) to avoid busy polling.\n\nThere are 1000 available concurrency slots, meaning that up to 1000 agents can be active at once, including you.\n\nFull-history forks (`fork_turns` omitted or `\"all\"`) inherit the parent model and reasoning effort and do not accept overrides. Only set `model` or `reasoning_effort` when explicitly requested by the user, applicable `AGENTS.md` instructions, or skill instructions; when doing so, set `fork_turns` to `\"none\"` or a positive integer string.</multi_agent_role>"}],"internal_chat_message_metadata_passthrough":{"content_item_kinds":["multi_agent.role_instructions"]}}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:51:45.187Z","ordinal":10,"type":"response_item","payload":{"type":"message","id":"msg_01a08971-6519-7cf3-9399-e7ea1213ab18","role":"developer","content":[{"type":"input_text","text":"<multi_agent_role>You are an agent in a team of agents collaborating to complete a task.\n\nYou can spawn sub-agents to handle subtasks, and those sub-agents can spawn their own sub-agents. All agents in the team, including the agents that you can assign tasks to, are equally intelligent and capable, and have access to the same set of tools.\n\nYou can use `spawn_agent` to create a new agent, `followup_task` to give an existing agent a new task and trigger a turn, and `send_message` to pass a message to a running agent.\n`send_message` calls may be read by a human, so ensure they are legible. Always put proper spaces between words and/or numbers.\nChild agents can also spawn their own sub-agents.\n\nWhen you provide a response in the final channel, that content is immediately delivered back to your parent agent.\nIn addition, your final answer may be read by a human, so ensure it is legible.\n\nYou will receive messages in the analysis channel in the form:\n```\nMessage Type: NEW_TASK | MESSAGE | FINAL_ANSWER\nTask name: <recipient>\nSender: <author>\nPayload:\n<payload text>\n```\nYou may also see them addressed as to=/root/..., which indicates your identity is /root/...\n\nNote that collaboration tools cannot be called from inside `functions.exec`. Call `spawn_agent`, `send_message`, `followup_task`, `wait_agent`, `interrupt_agent`, and `list_agents` only as direct tool calls using the recipient shown in their tool definitions, such as `to=functions.collaboration.spawn_agent`, since they are intentionally absent from the `functions.exec` `tools.*` namespace. Available tools in `functions.exec` are explicitly described with a `tools` namespace in the developer message.\n\nAll agents share the same directory. In detail:\n- All agents have access to the same container and filesystem as you.\n- All agents use the same current working directory.\n- As a result, edits made by one agent are immediately visible to all other agents.\n\nWhen calling `wait_agent`, prefer longer waits (minutes) to avoid busy polling.\n\nThere are 1000 available concurrency slots, meaning that up to 1000 agents can be active at once, including you.\n\nFull-history forks (`fork_turns` omitted or `\"all\"`) inherit the parent model and reasoning effort and do not accept overrides. Only set `model` or `reasoning_effort` when explicitly requested by the user, applicable `AGENTS.md` instructions, or skill instructions; when doing so, set `fork_turns` to `\"none\"` or a positive integer string.</multi_agent_role>"}],"internal_chat_message_metadata_passthrough":{"content_item_kinds":["multi_agent.role_instructions"]}}}
{"timestamp":"2026-09-10T03:51:47.627Z","ordinal":13,"type":"response_item","payload":{"type":"message","id":"msg_01a08971-6eaa-73c1-af7a-fbff19b79322","role":"developer","content":[{"type":"input_text","text":"<multi_agent_mode>Any earlier instruction enabling proactive multi-agent delegation no longer applies. Do not spawn sub-agents unless the user or applicable AGENTS.md/skill instructions explicitly ask for sub-agents, delegation, or parallel agent work.</multi_agent_mode>"}],"internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012307.6269631,"content_item_kinds":["multi_agent.mode_instructions"]}}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:51:47.627Z","ordinal":13,"type":"response_item","payload":{"type":"message","id":"msg_01a08971-6eaa-73c1-af7a-fbff19b79322","role":"developer","content":[{"type":"input_text","text":"<multi_agent_mode>Any earlier instruction enabling proactive multi-agent delegation no longer applies. Do not spawn sub-agents unless the user or applicable AGENTS.md/skill instructions explicitly ask for sub-agents, delegation, or parallel agent work.</multi_agent_mode>"}],"internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012307.6269631,"content_item_kinds":["multi_agent.mode_instructions"]}}}
{"timestamp":"2026-09-10T03:51:55.187Z","ordinal":20,"type":"event_msg","payload":{"type":"item_completed","thread_id":"01a08971-6519-7cf3-9399-e7f6b9686fbc","turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","item":{"type":"CommandExecution","id":"exec-4fd8a206-51da-47bd-9b97-2c8b960bcb43","process_id":"37497","command":["/usr/bin/bash","-lc","cat ENVIRONMENT.md"],"cwd":"file:///lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/kitchen","parsed_cmd":[{"type":"read","cmd":"cat ENVIRONMENT.md","name":"ENVIRONMENT.md","path":"ENVIRONMENT.md"}],"source":"unified_exec_startup","status":"completed","stdout":"# Machine environment for the scene benchmarks\n\nRead this before you start. It records what is already known to work on this machine,\nincluding failure modes that have already cost hours on earlier runs.\n\n## Where you are\n\nYou are running **inside a SLURM allocation on a GPU compute node**, not on the login node.\nThe GPUs are yours directly:\n\n- **8 x NVIDIA A100-SXM4-80GB**, driver 535.104.12, CUDA 12.2\n- Just run Blender normally. Do **not** submit `sbatch`/`srun` jobs -- you already hold the\n allocation. `nvidia-smi` works here; it does not work on the login node.\n\nThe allocation has a **wall-clock limit** (see `squeue -j $SLURM_JOB_ID -o %L`). Work so that\nyou survive being cut off: save the `.blend` and update `PROGRESS.md` at every milestone\nrather than holding everything to the end. If you are killed, the work must be resumable from\nwhat is on disk.\n\n## Blender\n\n```\n/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/blender-4.5.13-linux-x64/blender\n```\n\nOfficial blender.org 4.5.13 LTS, linux-x64. Ships both OptiX and CUDA Cycles kernels.\nUse `--background <file.blend> --python <script.py>`.\n\n## Three Cycles gotchas already hit on this exact machine\n\n**1. The OptiX *denoiser* does not work here.** OptiX *rendering* is fine and is what you want\n(`prefs.compute_device_type = 'OPTIX'` finds all 8 devices). But setting\n`scene.cycles.denoiser = 'OPTIX'` aborts the render with:\n\n```\nError: Failed to create OptiX denoiser\n```\n\nUse `OPENIMAGEDENOISE`. It is higher quality anyway. Also set\n`scene.cycles.denoising_use_gpu = True` if the attribute exists.\n\n**2. Do not detect the denoiser by reading the enum.** This idiom is broken on a headless\nofficial build:\n\n```python\nopts = scene.cycles.bl_rna.properties['denoiser'].enum_items.keys() # -> [] here!\nif opts: scene.cycles.use_denoising = True\nelse: scene.cycles.use_denoising = False # <- silently taken\n```\n\nThe enum comes back **empty**, so denoising gets silently disabled and you brute-force raw\nsamples for nothing. Assign the denoiser directly inside `try/except TypeError`, and print\nwhat you actually got.\n\n**3. `bpy.ops.wm.save_as_mainfile` can segfault on very large scenes.** A 179 MB / 5150-object\nscene with 18 packed textures crashed on save even though every edit before it succeeded. If\nyou hit this: save incrementally as the scene grows rather than only at the end, keep\nper-milestone checkpoint files, and avoid a single monolithic final save of an already-huge\nscene.\n\n## Measured performance baseline\n\nOn all 8 GPUs with OptiX + OIDN, a comparable-complexity architectural scene rendered\n**1920x1080 at 256 samples in roughly 40 s/frame** when each frame re-synced the scene. With\n`scene.render.use_persistent_data = True` and static geometry, the same scene ran **4.2\ns/frame**. So a 14-shot judgeset costs single-digit minutes per review cycle: there is no\nexcuse for a cheaper preview engine, and you can afford all 4+ cycles.\n\n## Network\n\nOutbound HTTPS works from this node. Poly Haven's API and CDN are reachable -- prefer real\nCC0 PBR textures over procedural. Verify with a quick request before committing to a pipeline.\n\n## No ffmpeg CLI\n\nThere is no `ffmpeg` binary on this cluster. If you need video, use Blender's own sequencer\n(it links ffmpeg internally) as the encoder.\n\n## What is being measured\n\nThis run is a **cost/time benchmark**. Your token usage and GPU time are being recorded\nautomatically -- you do not need to track them. What you *should* do is keep `PROGRESS.md`\ntimestamped at each milestone (scene built, cycle N rendered, cycle N reviewed), because those\ntimestamps are how the wall-clock is attributed to phases afterwards.\n\nDo not sandbag and do not pad. Work at the quality bar the brief states, stop when you reach\nit, and record honestly if you do not.\n","stderr":"","aggregated_output":"# Machine environment for the scene benchmarks\n\nRead this before you start. It records what is already known to work on this machine,\nincluding failure modes that have already cost hours on earlier runs.\n\n## Where you are\n\nYou are running **inside a SLURM allocation on a GPU compute node**, not on the login node.\nThe GPUs are yours directly:\n\n- **8 x NVIDIA A100-SXM4-80GB**, driver 535.104.12, CUDA 12.2\n- Just run Blender normally. Do **not** submit `sbatch`/`srun` jobs -- you already hold the\n allocation. `nvidia-smi` works here; it does not work on the login node.\n\nThe allocation has a **wall-clock limit** (see `squeue -j $SLURM_JOB_ID -o %L`). Work so that\nyou survive being cut off: save the `.blend` and update `PROGRESS.md` at every milestone\nrather than holding everything to the end. If you are killed, the work must be resumable from\nwhat is on disk.\n\n## Blender\n\n```\n/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/blender-4.5.13-linux-x64/blender\n```\n\nOfficial blender.org 4.5.13 LTS, linux-x64. Ships both OptiX and CUDA Cycles kernels.\nUse `--background <file.blend> --python <script.py>`.\n\n## Three Cycles gotchas already hit on this exact machine\n\n**1. The OptiX *denoiser* does not work here.** OptiX *rendering* is fine and is what you want\n(`prefs.compute_device_type = 'OPTIX'` finds all 8 devices). But setting\n`scene.cycles.denoiser = 'OPTIX'` aborts the render with:\n\n```\nError: Failed to create OptiX denoiser\n```\n\nUse `OPENIMAGEDENOISE`. It is higher quality anyway. Also set\n`scene.cycles.denoising_use_gpu = True` if the attribute exists.\n\n**2. Do not detect the denoiser by reading the enum.** This idiom is broken on a headless\nofficial build:\n\n```python\nopts = scene.cycles.bl_rna.properties['denoiser'].enum_items.keys() # -> [] here!\nif opts: scene.cycles.use_denoising = True\nelse: scene.cycles.use_denoising = False # <- silently taken\n```\n\nThe enum comes back **empty**, so denoising gets silently disabled and you brute-force raw\nsamples for nothing. Assign the denoiser directly inside `try/except TypeError`, and print\nwhat you actually got.\n\n**3. `bpy.ops.wm.save_as_mainfile` can segfault on very large scenes.** A 179 MB / 5150-object\nscene with 18 packed textures crashed on save even though every edit before it succeeded. If\nyou hit this: save incrementally as the scene grows rather than only at the end, keep\nper-milestone checkpoint files, and avoid a single monolithic final save of an already-huge\nscene.\n\n## Measured performance baseline\n\nOn all 8 GPUs with OptiX + OIDN, a comparable-complexity architectural scene rendered\n**1920x1080 at 256 samples in roughly 40 s/frame** when each frame re-synced the scene. With\n`scene.render.use_persistent_data = True` and static geometry, the same scene ran **4.2\ns/frame**. So a 14-shot judgeset costs single-digit minutes per review cycle: there is no\nexcuse for a cheaper preview engine, and you can afford all 4+ cycles.\n\n## Network\n\nOutbound HTTPS works from this node. Poly Haven's API and CDN are reachable -- prefer real\nCC0 PBR textures over procedural. Verify with a quick request before committing to a pipeline.\n\n## No ffmpeg CLI\n\nThere is no `ffmpeg` binary on this cluster. If you need video, use Blender's own sequencer\n(it links ffmpeg internally) as the encoder.\n\n## What is being measured\n\nThis run is a **cost/time benchmark**. Your token usage and GPU time are being recorded\nautomatically -- you do not need to track them. What you *should* do is keep `PROGRESS.md`\ntimestamped at each milestone (scene built, cycle N rendered, cycle N reviewed), because those\ntimestamps are how the wall-clock is attributed to phases afterwards.\n\nDo not sandbag and do not pad. Work at the quality bar the brief states, stop when you reach\nit, and record honestly if you do not.\n","exit_code":0,"duration":{"secs":0,"nanos":77809509},"formatted_output":"# Machine environment for the scene benchmarks\n\nRead this before you start. It records what is already known to work on this machine,\nincluding failure modes that have already cost hours on earlier runs.\n\n## Where you are\n\nYou are running **inside a SLURM allocation on a GPU compute node**, not on the login node.\nThe GPUs are yours directly:\n\n- **8 x NVIDIA A100-SXM4-80GB**, driver 535.104.12, CUDA 12.2\n- Just run Blender normally. Do **not** submit `sbatch`/`srun` jobs -- you already hold the\n allocation. `nvidia-smi` works here; it does not work on the login node.\n\nThe allocation has a **wall-clock limit** (see `squeue -j $SLURM_JOB_ID -o %L`). Work so that\nyou survive being cut off: save the `.blend` and update `PROGRESS.md` at every milestone\nrather than holding everything to the end. If you are killed, the work must be resumable from\nwhat is on disk.\n\n## Blender\n\n```\n/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/blender-4.5.13-linux-x64/blender\n```\n\nOfficial blender.org 4.5.13 LTS, linux-x64. Ships both OptiX and CUDA Cycles kernels.\nUse `--background <file.blend> --python <script.py>`.\n\n## Three Cycles gotchas already hit on this exact machine\n\n**1. The OptiX *denoiser* does not work here.** OptiX *rendering* is fine and is what you want\n(`prefs.compute_device_type = 'OPTIX'` finds all 8 devices). But setting\n`scene.cycles.denoiser = 'OPTIX'` aborts the render with:\n\n```\nError: Failed to create OptiX denoiser\n```\n\nUse `OPENIMAGEDENOISE`. It is higher quality anyway. Also set\n`scene.cycles.denoising_use_gpu = True` if the attribute exists.\n\n**2. Do not detect the denoiser by reading the enum.** This idiom is broken on a headless\nofficial build:\n\n```python\nopts = scene.cycles.bl_rna.properties['denoiser'].enum_items.keys() # -> [] here!\nif opts: scene.cycles.use_denoising = True\nelse: scene.cycles.use_denoising = False # <- silently taken\n```\n\nThe enum comes back **empty**, so denoising gets silently disabled and you brute-force raw\nsamples for nothing. Assign the denoiser directly inside `try/except TypeError`, and print\nwhat you actually got.\n\n**3. `bpy.ops.wm.save_as_mainfile` can segfault on very large scenes.** A 179 MB / 5150-object\nscene with 18 packed textures crashed on save even though every edit before it succeeded. If\nyou hit this: save incrementally as the scene grows rather than only at the end, keep\nper-milestone checkpoint files, and avoid a single monolithic final save of an already-huge\nscene.\n\n## Measured performance baseline\n\nOn all 8 GPUs with OptiX + OIDN, a comparable-complexity architectural scene rendered\n**1920x1080 at 256 samples in roughly 40 s/frame** when each frame re-synced the scene. With\n`scene.render.use_persistent_data = True` and static geometry, the same scene ran **4.2\ns/frame**. So a 14-shot judgeset costs single-digit minutes per review cycle: there is no\nexcuse for a cheaper preview engine, and you can afford all 4+ cycles.\n\n## Network\n\nOutbound HTTPS works from this node. Poly Haven's API and CDN are reachable -- prefer real\nCC0 PBR textures over procedural. Verify with a quick request before committing to a pipeline.\n\n## No ffmpeg CLI\n\nThere is no `ffmpeg` binary on this cluster. If you need video, use Blender's own sequencer\n(it links ffmpeg internally) as the encoder.\n\n## What is being measured\n\nThis run is a **cost/time benchmark**. Your token usage and GPU time are being recorded\nautomatically -- you do not need to track them. What you *should* do is keep `PROGRESS.md`\ntimestamped at each milestone (scene built, cycle N rendered, cycle N reviewed), because those\ntimestamps are how the wall-clock is attributed to phases afterwards.\n\nDo not sandbag and do not pad. Work at the quality bar the brief states, stop when you reach\nit, and record honestly if you do not.\n"},"started_at_ms":1789012315109,"completed_at_ms":1789012315187}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:51:55.187Z","ordinal":20,"type":"event_msg","payload":{"type":"item_completed","thread_id":"01a08971-6519-7cf3-9399-e7f6b9686fbc","turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","item":{"type":"CommandExecution","id":"exec-4fd8a206-51da-47bd-9b97-2c8b960bcb43","process_id":"37497","command":["/usr/bin/bash","-lc","cat ENVIRONMENT.md"],"cwd":"file:///lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/kitchen","parsed_cmd":[{"type":"read","cmd":"cat ENVIRONMENT.md","name":"ENVIRONMENT.md","path":"ENVIRONMENT.md"}],"source":"unified_exec_startup","status":"completed","stdout":"# Machine environment for the scene benchmarks\n\nRead this before you start. It records what is already known to work on this machine,\nincluding failure modes that have already cost hours on earlier runs.\n\n## Where you are\n\nYou are running **inside a SLURM allocation on a GPU compute node**, not on the login node.\nThe GPUs are yours directly:\n\n- **8 x NVIDIA A100-SXM4-80GB**, driver 535.104.12, CUDA 12.2\n- Just run Blender normally. Do **not** submit `sbatch`/`srun` jobs -- you already hold the\n allocation. `nvidia-smi` works here; it does not work on the login node.\n\nThe allocation has a **wall-clock limit** (see `squeue -j $SLURM_JOB_ID -o %L`). Work so that\nyou survive being cut off: save the `.blend` and update `PROGRESS.md` at every milestone\nrather than holding everything to the end. If you are killed, the work must be resumable from\nwhat is on disk.\n\n## Blender\n\n```\n/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/blender-4.5.13-linux-x64/blender\n```\n\nOfficial blender.org 4.5.13 LTS, linux-x64. Ships both OptiX and CUDA Cycles kernels.\nUse `--background <file.blend> --python <script.py>`.\n\n## Three Cycles gotchas already hit on this exact machine\n\n**1. The OptiX *denoiser* does not work here.** OptiX *rendering* is fine and is what you want\n(`prefs.compute_device_type = 'OPTIX'` finds all 8 devices). But setting\n`scene.cycles.denoiser = 'OPTIX'` aborts the render with:\n\n```\nError: Failed to create OptiX denoiser\n```\n\nUse `OPENIMAGEDENOISE`. It is higher quality anyway. Also set\n`scene.cycles.denoising_use_gpu = True` if the attribute exists.\n\n**2. Do not detect the denoiser by reading the enum.** This idiom is broken on a headless\nofficial build:\n\n```python\nopts = scene.cycles.bl_rna.properties['denoiser'].enum_items.keys() # -> [] here!\nif opts: scene.cycles.use_denoising = True\nelse: scene.cycles.use_denoising = False # <- silently taken\n```\n\nThe enum comes back **empty**, so denoising gets silently disabled and you brute-force raw\nsamples for nothing. Assign the denoiser directly inside `try/except TypeError`, and print\nwhat you actually got.\n\n**3. `bpy.ops.wm.save_as_mainfile` can segfault on very large scenes.** A 179 MB / 5150-object\nscene with 18 packed textures crashed on save even though every edit before it succeeded. If\nyou hit this: save incrementally as the scene grows rather than only at the end, keep\nper-milestone checkpoint files, and avoid a single monolithic final save of an already-huge\nscene.\n\n## Measured performance baseline\n\nOn all 8 GPUs with OptiX + OIDN, a comparable-complexity architectural scene rendered\n**1920x1080 at 256 samples in roughly 40 s/frame** when each frame re-synced the scene. With\n`scene.render.use_persistent_data = True` and static geometry, the same scene ran **4.2\ns/frame**. So a 14-shot judgeset costs single-digit minutes per review cycle: there is no\nexcuse for a cheaper preview engine, and you can afford all 4+ cycles.\n\n## Network\n\nOutbound HTTPS works from this node. Poly Haven's API and CDN are reachable -- prefer real\nCC0 PBR textures over procedural. Verify with a quick request before committing to a pipeline.\n\n## No ffmpeg CLI\n\nThere is no `ffmpeg` binary on this cluster. If you need video, use Blender's own sequencer\n(it links ffmpeg internally) as the encoder.\n\n## What is being measured\n\nThis run is a **cost/time benchmark**. Your token usage and GPU time are being recorded\nautomatically -- you do not need to track them. What you *should* do is keep `PROGRESS.md`\ntimestamped at each milestone (scene built, cycle N rendered, cycle N reviewed), because those\ntimestamps are how the wall-clock is attributed to phases afterwards.\n\nDo not sandbag and do not pad. Work at the quality bar the brief states, stop when you reach\nit, and record honestly if you do not.\n","stderr":"","aggregated_output":"# Machine environment for the scene benchmarks\n\nRead this before you start. It records what is already known to work on this machine,\nincluding failure modes that have already cost hours on earlier runs.\n\n## Where you are\n\nYou are running **inside a SLURM allocation on a GPU compute node**, not on the login node.\nThe GPUs are yours directly:\n\n- **8 x NVIDIA A100-SXM4-80GB**, driver 535.104.12, CUDA 12.2\n- Just run Blender normally. Do **not** submit `sbatch`/`srun` jobs -- you already hold the\n allocation. `nvidia-smi` works here; it does not work on the login node.\n\nThe allocation has a **wall-clock limit** (see `squeue -j $SLURM_JOB_ID -o %L`). Work so that\nyou survive being cut off: save the `.blend` and update `PROGRESS.md` at every milestone\nrather than holding everything to the end. If you are killed, the work must be resumable from\nwhat is on disk.\n\n## Blender\n\n```\n/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/blender-4.5.13-linux-x64/blender\n```\n\nOfficial blender.org 4.5.13 LTS, linux-x64. Ships both OptiX and CUDA Cycles kernels.\nUse `--background <file.blend> --python <script.py>`.\n\n## Three Cycles gotchas already hit on this exact machine\n\n**1. The OptiX *denoiser* does not work here.** OptiX *rendering* is fine and is what you want\n(`prefs.compute_device_type = 'OPTIX'` finds all 8 devices). But setting\n`scene.cycles.denoiser = 'OPTIX'` aborts the render with:\n\n```\nError: Failed to create OptiX denoiser\n```\n\nUse `OPENIMAGEDENOISE`. It is higher quality anyway. Also set\n`scene.cycles.denoising_use_gpu = True` if the attribute exists.\n\n**2. Do not detect the denoiser by reading the enum.** This idiom is broken on a headless\nofficial build:\n\n```python\nopts = scene.cycles.bl_rna.properties['denoiser'].enum_items.keys() # -> [] here!\nif opts: scene.cycles.use_denoising = True\nelse: scene.cycles.use_denoising = False # <- silently taken\n```\n\nThe enum comes back **empty**, so denoising gets silently disabled and you brute-force raw\nsamples for nothing. Assign the denoiser directly inside `try/except TypeError`, and print\nwhat you actually got.\n\n**3. `bpy.ops.wm.save_as_mainfile` can segfault on very large scenes.** A 179 MB / 5150-object\nscene with 18 packed textures crashed on save even though every edit before it succeeded. If\nyou hit this: save incrementally as the scene grows rather than only at the end, keep\nper-milestone checkpoint files, and avoid a single monolithic final save of an already-huge\nscene.\n\n## Measured performance baseline\n\nOn all 8 GPUs with OptiX + OIDN, a comparable-complexity architectural scene rendered\n**1920x1080 at 256 samples in roughly 40 s/frame** when each frame re-synced the scene. With\n`scene.render.use_persistent_data = True` and static geometry, the same scene ran **4.2\ns/frame**. So a 14-shot judgeset costs single-digit minutes per review cycle: there is no\nexcuse for a cheaper preview engine, and you can afford all 4+ cycles.\n\n## Network\n\nOutbound HTTPS works from this node. Poly Haven's API and CDN are reachable -- prefer real\nCC0 PBR textures over procedural. Verify with a quick request before committing to a pipeline.\n\n## No ffmpeg CLI\n\nThere is no `ffmpeg` binary on this cluster. If you need video, use Blender's own sequencer\n(it links ffmpeg internally) as the encoder.\n\n## What is being measured\n\nThis run is a **cost/time benchmark**. Your token usage and GPU time are being recorded\nautomatically -- you do not need to track them. What you *should* do is keep `PROGRESS.md`\ntimestamped at each milestone (scene built, cycle N rendered, cycle N reviewed), because those\ntimestamps are how the wall-clock is attributed to phases afterwards.\n\nDo not sandbag and do not pad. Work at the quality bar the brief states, stop when you reach\nit, and record honestly if you do not.\n","exit_code":0,"duration":{"secs":0,"nanos":77809509},"formatted_output":"# Machine environment for the scene benchmarks\n\nRead this before you start. It records what is already known to work on this machine,\nincluding failure modes that have already cost hours on earlier runs.\n\n## Where you are\n\nYou are running **inside a SLURM allocation on a GPU compute node**, not on the login node.\nThe GPUs are yours directly:\n\n- **8 x NVIDIA A100-SXM4-80GB**, driver 535.104.12, CUDA 12.2\n- Just run Blender normally. Do **not** submit `sbatch`/`srun` jobs -- you already hold the\n allocation. `nvidia-smi` works here; it does not work on the login node.\n\nThe allocation has a **wall-clock limit** (see `squeue -j $SLURM_JOB_ID -o %L`). Work so that\nyou survive being cut off: save the `.blend` and update `PROGRESS.md` at every milestone\nrather than holding everything to the end. If you are killed, the work must be resumable from\nwhat is on disk.\n\n## Blender\n\n```\n/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/blender-4.5.13-linux-x64/blender\n```\n\nOfficial blender.org 4.5.13 LTS, linux-x64. Ships both OptiX and CUDA Cycles kernels.\nUse `--background <file.blend> --python <script.py>`.\n\n## Three Cycles gotchas already hit on this exact machine\n\n**1. The OptiX *denoiser* does not work here.** OptiX *rendering* is fine and is what you want\n(`prefs.compute_device_type = 'OPTIX'` finds all 8 devices). But setting\n`scene.cycles.denoiser = 'OPTIX'` aborts the render with:\n\n```\nError: Failed to create OptiX denoiser\n```\n\nUse `OPENIMAGEDENOISE`. It is higher quality anyway. Also set\n`scene.cycles.denoising_use_gpu = True` if the attribute exists.\n\n**2. Do not detect the denoiser by reading the enum.** This idiom is broken on a headless\nofficial build:\n\n```python\nopts = scene.cycles.bl_rna.properties['denoiser'].enum_items.keys() # -> [] here!\nif opts: scene.cycles.use_denoising = True\nelse: scene.cycles.use_denoising = False # <- silently taken\n```\n\nThe enum comes back **empty**, so denoising gets silently disabled and you brute-force raw\nsamples for nothing. Assign the denoiser directly inside `try/except TypeError`, and print\nwhat you actually got.\n\n**3. `bpy.ops.wm.save_as_mainfile` can segfault on very large scenes.** A 179 MB / 5150-object\nscene with 18 packed textures crashed on save even though every edit before it succeeded. If\nyou hit this: save incrementally as the scene grows rather than only at the end, keep\nper-milestone checkpoint files, and avoid a single monolithic final save of an already-huge\nscene.\n\n## Measured performance baseline\n\nOn all 8 GPUs with OptiX + OIDN, a comparable-complexity architectural scene rendered\n**1920x1080 at 256 samples in roughly 40 s/frame** when each frame re-synced the scene. With\n`scene.render.use_persistent_data = True` and static geometry, the same scene ran **4.2\ns/frame**. So a 14-shot judgeset costs single-digit minutes per review cycle: there is no\nexcuse for a cheaper preview engine, and you can afford all 4+ cycles.\n\n## Network\n\nOutbound HTTPS works from this node. Poly Haven's API and CDN are reachable -- prefer real\nCC0 PBR textures over procedural. Verify with a quick request before committing to a pipeline.\n\n## No ffmpeg CLI\n\nThere is no `ffmpeg` binary on this cluster. If you need video, use Blender's own sequencer\n(it links ffmpeg internally) as the encoder.\n\n## What is being measured\n\nThis run is a **cost/time benchmark**. Your token usage and GPU time are being recorded\nautomatically -- you do not need to track them. What you *should* do is keep `PROGRESS.md`\ntimestamped at each milestone (scene built, cycle N rendered, cycle N reviewed), because those\ntimestamps are how the wall-clock is attributed to phases afterwards.\n\nDo not sandbag and do not pad. Work at the quality bar the brief states, stop when you reach\nit, and record honestly if you do not.\n"},"started_at_ms":1789012315109,"completed_at_ms":1789012315187}}
{"timestamp":"2026-09-10T03:51:55.205Z","ordinal":21,"type":"response_item","payload":{"type":"custom_tool_call_output","id":"ctco_01a08971-8c45-7bf0-914f-cf8f6b137958","call_id":"call_DSgtMSlGFG6lrSfR10QlrZrd","output":[{"type":"input_text","text":"Script completed\nWall time 0.3 seconds\nOutput:\n"},{"type":"input_text","text":"# Machine environment for the scene benchmarks\n\nRead this before you start. It records what is already known to work on this machine,\nincluding failure modes that have already cost hours on earlier runs.\n\n## Where you are\n\nYou are running **inside a SLURM allocation on a GPU compute node**, not on the login node.\nThe GPUs are yours directly:\n\n- **8 x NVIDIA A100-SXM4-80GB**, driver 535.104.12, CUDA 12.2\n- Just run Blender normally. Do **not** submit `sbatch`/`srun` jobs -- you already hold the\n allocation. `nvidia-smi` works here; it does not work on the login node.\n\nThe allocation has a **wall-clock limit** (see `squeue -j $SLURM_JOB_ID -o %L`). Work so that\nyou survive being cut off: save the `.blend` and update `PROGRESS.md` at every milestone\nrather than holding everything to the end. If you are killed, the work must be resumable from\nwhat is on disk.\n\n## Blender\n\n```\n/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/blender-4.5.13-linux-x64/blender\n```\n\nOfficial blender.org 4.5.13 LTS, linux-x64. Ships both OptiX and CUDA Cycles kernels.\nUse `--background <file.blend> --python <script.py>`.\n\n## Three Cycles gotchas already hit on this exact machine\n\n**1. The OptiX *denoiser* does not work here.** OptiX *rendering* is fine and is what you want\n(`prefs.compute_device_type = 'OPTIX'` finds all 8 devices). But setting\n`scene.cycles.denoiser = 'OPTIX'` aborts the render with:\n\n```\nError: Failed to create OptiX denoiser\n```\n\nUse `OPENIMAGEDENOISE`. It is higher quality anyway. Also set\n`scene.cycles.denoising_use_gpu = True` if the attribute exists.\n\n**2. Do not detect the denoiser by reading the enum.** This idiom is broken on a headless\nofficial build:\n\n```python\nopts = scene.cycles.bl_rna.properties['denoiser'].enum_items.keys() # -> [] here!\nif opts: scene.cycles.use_denoising = True\nelse: scene.cycles.use_denoising = False # <- silently taken\n```\n\nThe enum comes back **empty**, so denoising gets silently disabled and you brute-force raw\nsamples for nothing. Assign the denoiser directly inside `try/except TypeError`, and print\nwhat you actually got.\n\n**3. `bpy.ops.wm.save_as_mainfile` can segfault on very large scenes.** A 179 MB / 5150-object\nscene with 18 packed textures crashed on save even though every edit before it succeeded. If\nyou hit this: save incrementally as the scene grows rather than only at the end, keep\nper-milestone checkpoint files, and avoid a single monolithic final save of an already-huge\nscene.\n\n## Measured performance baseline\n\nOn all 8 GPUs with OptiX + OIDN, a comparable-complexity architectural scene rendered\n**1920x1080 at 256 samples in roughly 40 s/frame** when each frame re-synced the scene. With\n`scene.render.use_persistent_data = True` and static geometry, the same scene ran **4.2\ns/frame**. So a 14-shot judgeset costs single-digit minutes per review cycle: there is no\nexcuse for a cheaper preview engine, and you can afford all 4+ cycles.\n\n## Network\n\nOutbound HTTPS works from this node. Poly Haven's API and CDN are reachable -- prefer real\nCC0 PBR textures over procedural. Verify with a quick request before committing to a pipeline.\n\n## No ffmpeg CLI\n\nThere is no `ffmpeg` binary on this cluster. If you need video, use Blender's own sequencer\n(it links ffmpeg internally) as the encoder.\n\n## What is being measured\n\nThis run is a **cost/time benchmark**. Your token usage and GPU time are being recorded\nautomatically -- you do not need to track them. What you *should* do is keep `PROGRESS.md`\ntimestamped at each milestone (scene built, cycle N rendered, cycle N reviewed), because those\ntimestamps are how the wall-clock is attributed to phases afterwards.\n\nDo not sandbag and do not pad. Work at the quality bar the brief states, stop when you reach\nit, and record honestly if you do not.\n"}],"internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012315.205438}}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:51:55.205Z","ordinal":21,"type":"response_item","payload":{"type":"custom_tool_call_output","id":"ctco_01a08971-8c45-7bf0-914f-cf8f6b137958","call_id":"call_DSgtMSlGFG6lrSfR10QlrZrd","output":[{"type":"input_text","text":"Script completed\nWall time 0.3 seconds\nOutput:\n"},{"type":"input_text","text":"# Machine environment for the scene benchmarks\n\nRead this before you start. It records what is already known to work on this machine,\nincluding failure modes that have already cost hours on earlier runs.\n\n## Where you are\n\nYou are running **inside a SLURM allocation on a GPU compute node**, not on the login node.\nThe GPUs are yours directly:\n\n- **8 x NVIDIA A100-SXM4-80GB**, driver 535.104.12, CUDA 12.2\n- Just run Blender normally. Do **not** submit `sbatch`/`srun` jobs -- you already hold the\n allocation. `nvidia-smi` works here; it does not work on the login node.\n\nThe allocation has a **wall-clock limit** (see `squeue -j $SLURM_JOB_ID -o %L`). Work so that\nyou survive being cut off: save the `.blend` and update `PROGRESS.md` at every milestone\nrather than holding everything to the end. If you are killed, the work must be resumable from\nwhat is on disk.\n\n## Blender\n\n```\n/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/blender-4.5.13-linux-x64/blender\n```\n\nOfficial blender.org 4.5.13 LTS, linux-x64. Ships both OptiX and CUDA Cycles kernels.\nUse `--background <file.blend> --python <script.py>`.\n\n## Three Cycles gotchas already hit on this exact machine\n\n**1. The OptiX *denoiser* does not work here.** OptiX *rendering* is fine and is what you want\n(`prefs.compute_device_type = 'OPTIX'` finds all 8 devices). But setting\n`scene.cycles.denoiser = 'OPTIX'` aborts the render with:\n\n```\nError: Failed to create OptiX denoiser\n```\n\nUse `OPENIMAGEDENOISE`. It is higher quality anyway. Also set\n`scene.cycles.denoising_use_gpu = True` if the attribute exists.\n\n**2. Do not detect the denoiser by reading the enum.** This idiom is broken on a headless\nofficial build:\n\n```python\nopts = scene.cycles.bl_rna.properties['denoiser'].enum_items.keys() # -> [] here!\nif opts: scene.cycles.use_denoising = True\nelse: scene.cycles.use_denoising = False # <- silently taken\n```\n\nThe enum comes back **empty**, so denoising gets silently disabled and you brute-force raw\nsamples for nothing. Assign the denoiser directly inside `try/except TypeError`, and print\nwhat you actually got.\n\n**3. `bpy.ops.wm.save_as_mainfile` can segfault on very large scenes.** A 179 MB / 5150-object\nscene with 18 packed textures crashed on save even though every edit before it succeeded. If\nyou hit this: save incrementally as the scene grows rather than only at the end, keep\nper-milestone checkpoint files, and avoid a single monolithic final save of an already-huge\nscene.\n\n## Measured performance baseline\n\nOn all 8 GPUs with OptiX + OIDN, a comparable-complexity architectural scene rendered\n**1920x1080 at 256 samples in roughly 40 s/frame** when each frame re-synced the scene. With\n`scene.render.use_persistent_data = True` and static geometry, the same scene ran **4.2\ns/frame**. So a 14-shot judgeset costs single-digit minutes per review cycle: there is no\nexcuse for a cheaper preview engine, and you can afford all 4+ cycles.\n\n## Network\n\nOutbound HTTPS works from this node. Poly Haven's API and CDN are reachable -- prefer real\nCC0 PBR textures over procedural. Verify with a quick request before committing to a pipeline.\n\n## No ffmpeg CLI\n\nThere is no `ffmpeg` binary on this cluster. If you need video, use Blender's own sequencer\n(it links ffmpeg internally) as the encoder.\n\n## What is being measured\n\nThis run is a **cost/time benchmark**. Your token usage and GPU time are being recorded\nautomatically -- you do not need to track them. What you *should* do is keep `PROGRESS.md`\ntimestamped at each milestone (scene built, cycle N rendered, cycle N reviewed), because those\ntimestamps are how the wall-clock is attributed to phases afterwards.\n\nDo not sandbag and do not pad. Work at the quality bar the brief states, stop when you reach\nit, and record honestly if you do not.\n"}],"internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012315.205438}}}
{"timestamp":"2026-09-10T03:52:03.479Z","ordinal":25,"type":"event_msg","payload":{"type":"item_completed","thread_id":"01a08971-6519-7cf3-9399-e7f6b9686fbc","turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","item":{"type":"CommandExecution","id":"exec-80770884-59c5-49e9-a4f3-4ddd55ac1c1e","process_id":"25996","command":["/usr/bin/bash","-lc","cat /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/sisyphuslabs/omo/4.16.1/skills/programming/SKILL.md"],"cwd":"file:///lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/kitchen","parsed_cmd":[{"type":"read","cmd":"cat /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/sisyphuslabs/omo/4.16.1/skills/programming/SKILL.md","name":"SKILL.md","path":"/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/sisyphuslabs/omo/4.16.1/skills/programming/SKILL.md"}],"source":"unified_exec_startup","status":"completed","stdout":"---\nname: programming\ndescription: \"MUST USE for ANY work on .py .pyi .rs .ts .tsx .mts .cts .go files. One philosophy: strict types, modern stacks (Pydantic v2 / serde+thiserror / Zod / gin+sqlc+pgx+slog), modern toolchains (uv+basedpyright+ruff / cargo+clippy+miri / Bun+Biome+tsc / gofumpt+golangci-lint v2+nilaway+go-race), parse-don't-validate, exhaustive match, typed errors, no any/unwrap/panic, 250 LOC ceiling, TDD, consumer-routed logging. Routes to references/{python,rust,typescript,rust-ub,go}/ + references/logging.md. Triggers: write/edit Python/Rust/TypeScript/Go code, new project, gin server, bubbletea TUI, CJK IME, connect-go RPC, sqlc pgx, branded ids, exhaustive match, unsafe Rust, miri, oversized file, refactor, TDD, e2e test, logging, log levels, structured logging, observability, arena, allocator, bumpalo, const fn, const generics, comptime, zero-alloc, bitfield, repr, scopeguard, errdefer, Zig-like, zerocopy, packed struct.\"\n---\n\n# Programming\n\nYou are a lazy senior engineer — lazy meaning efficient, never careless. **The best code is the code never written; the code you do write is type-strict, stack-first, async-correct, and architecturally honest about size.**\n\nThis skill is an index. The hard per-language rules live under `references/`. Load the language-specific reference **before** writing a single line of code.\n\n---\n\n## PHASE 0 — LANGUAGE GATE (RUN THIS FIRST, EVERY TIME)\n\n**DO NOT WRITE OR EDIT A SINGLE LINE OF CODE BEFORE COMPLETING THIS GATE.**\n\n1. **Identify the language** from the file extension or the user's request.\n2. **STOP** and read the matching reference set:\n\n | File / Language | MANDATORY reading (load `Read` tool on every file below) |\n |---|---|\n | `.py`, `.pyi`, \"Python\" | `references/python/README.md` + every file under `references/python/` that the README tells you to load on demand |\n | `.rs`, `Cargo.toml`, \"Rust\" | `references/rust/README.md` + every file under `references/rust/` that the README tells you to load on demand. **IF the change touches `unsafe`, `*mut`, `*const`, `MaybeUninit`, FFI, `unsafe impl Send/Sync`, or a custom lock-free primitive: ALSO load `references/rust-ub/README.md` plus every file under `references/rust-ub/`.** |\n | `.ts`, `.tsx`, `.mts`, `.cts`, \"TypeScript\" | `references/typescript/README.md` + every file under `references/typescript/` that the README tells you to load on demand |\n | `.go`, `go.mod`, `go.sum`, `.golangci.yml`, `*.proto` next to a Go module, \"Go\" / \"Golang\" | `references/go/README.md` + every file under `references/go/` that the README tells you to load on demand |\n\n3. Only after the references are loaded, apply the **shared philosophy** below plus the per-language iron list from the reference.\n\n**No exceptions for \"small\" or \"one-off\" code.** The whole point of the modern toolchain (uv + PEP 723, `rust-script`, Bun) is that disposable scripts cost nothing to write with full discipline.\n\n---\n\n## Shared philosophy (all three languages)\n\nThese are not style preferences. They are the seven axioms every recipe in `references/` derives from.\n\n0. **The best code is the code never written.** Before writing, stop at the first rung that holds: (1) does this need to exist at all? (YAGNI) (2) does this codebase already have it? — reuse the helper or pattern, do not re-implement. (3) does the standard library do it? (4) does a native platform feature cover it? (5) does an installed dependency solve it? (6) can it be one line? (7) only then, write the minimum that works. Climb the ladder *after* you understand the problem and trace the real flow end to end — the smallest diff in the wrong place is a second bug, not laziness. The ladder is a fast decision, not a written essay: pick the rung and move. **Bug fix = root cause, not symptom.** A ticket names a symptom; grep every caller of the function you touch and fix the shared seam once — one guard at the source is a smaller, more correct diff than one guard per caller, and patching only the path the ticket names leaves a sibling caller broken.\n\n1. **The type system is your proof system.** Make illegal states unrepresentable. The compiler / type checker is the cheapest test you will ever run. If a bug can be expressed as a type error, it is *required* to be expressed as a type error.\n\n2. **Parse, don't validate.** Untrusted input crosses a boundary exactly once - at the boundary it is parsed into a typed value (Pydantic v2 in Python, `serde` + `#[derive]` in Rust, Zod in TypeScript). Inside the boundary, code receives typed values and never re-validates. The boundary owns trust; the interior owns logic.\n\n3. **One name = one concept.** A `UserId` is not a `string`. A `Seconds` is not a `Milliseconds`. Use `NewType` (Python), newtype tuple structs (Rust), or branded types (TypeScript) for every distinct semantic primitive. The compiler refuses to let two semantic units mix.\n\n4. **Exhaustive variant matching, always.** Discriminated unions and enums are matched exhaustively. Python: `match` + `case unreachable: assert_never(unreachable)`. Rust: `match` (the compiler enforces). TypeScript: `switch` + `assertNever`. **`if`/`elif`/`else` is forbidden for discriminating on a tagged variant** - it silently swallows new variants.\n\n5. **Trust framework guarantees. Validate only at boundaries.** No null checks for values the type system already proves non-null. No `try/except` around code that cannot raise. No `unwrap`/`!`/`as` to paper over a contract you should have encoded in types. No defensive layer for a scenario you cannot name.\n\n6. **Test-driven, with the right shape of test.** No production line ships without a failing test that proves it was needed. Behavior is locked by tests, not by hope. See the TDD discipline below.\n\n---\n\n## TDD DISCIPLINE — NON-NEGOTIABLE\n\n**Every change follows the red → green → refactor loop.** The order is mandatory; reverse it and you have written speculative code.\n\n### The order\n\n1. **Red.** Write a failing test that names the behavior in `Given / When / Then`. Run it. *Confirm it fails for the right reason* — not a typo, not an import error. A test that fails because the function does not exist yet is the right reason. A test that fails because of a missing import is not.\n2. **Green.** Write the minimum code to make the test pass. Resist adding the second case until the first passes. The second case is the next red.\n3. **Refactor.** With the test green, restructure ruthlessly. The test is your safety net. If the test is hard to refactor against, the test is bad — fix the test before the code.\n\n### The shape of the test pyramid\n\nEvery feature ships with all three rungs, sized in this proportion:\n\n| Rung | Count | Purpose | Speed budget |\n|---|---|---|---|\n| **Unit** | many | Pure-function correctness for every meaningful input class (happy + edges + boundaries + error paths) | < 10 ms each |\n| **Integration** | some | The real adapter against the real downstream (DB, queue, HTTP) — via `testcontainers`, `httptest`, or equivalent. NEVER a unit test pretending to be integration. | < 1 s each |\n| **E2E scenario** | few | One narrative per user-visible outcome. Spins the binary or the full app; drives it through its real surface (HTTP route, CLI invocation, TUI keystroke). Asserts the *observable outcome*, not internal state. | seconds, run on CI |\n\nIf a feature has zero E2E coverage, it is undone — even if every unit test passes.\n\n### Given / When / Then is mandatory\n\nEvery test — unit, integration, E2E — is structured by these three blocks. Names follow `Test_<Behavior>_when_<Condition>` or the language idiom (`it(\"<does X> when <Y>\")`, `#[test] fn behavior_when_condition`).\n\n```\nGiven: the preconditions and fixtures\nWhen: the single action under test\nThen: the observable outcome AND only that outcome\n```\n\nOne `When` per test. Multiple `When`s = multiple tests. The `Then` asserts only what changed because of the `When` — not unrelated invariants.\n\n### Less mock, the better\n\nMocks are a last resort, not a default. The priority order:\n\n1. **Real object.** Use it when constructable in <1 ms (most domain types, pure functions, value objects).\n2. **In-memory fake.** A real implementation of the interface backed by a map/slice — for stores, caches, queues. The fake has its OWN test that proves it behaves like the real one.\n3. **Testcontainer / sandbox.** Real Postgres, real Redis, real S3-compatible (MinIO), via `testcontainers`. Slow but truthful.\n4. **HTTP-level fake.** `httptest.Server` (Go), `respx` (Python), `msw` (TS) — fake at the wire, not at the SDK.\n5. **Mock.** Only when 1–4 are genuinely infeasible (clock, randomness, external SaaS with no sandbox). Then mock the **narrowest** seam — never an entire service. A mock that returns whatever the test wants is a tautology and proves nothing.\n\n**The rule**: if your test fails when the production code's *implementation* changes but its *behavior* did not, the test is over-mocked. Delete the mock; assert on observable outputs.\n\n### Efficient AND accurate — both, not either\n\n- **Accurate**: the test fails for the bug it names, and only that bug. No incidental coupling to format, ordering, whitespace, or unrelated fields. Assert on the *contract*, not on the dump.\n- **Efficient**: the whole unit suite runs in < 30 seconds on a developer laptop. The whole integration suite in < 5 minutes. If you cross those budgets, profile and split — fast tests run on every save, slow ones run on push.\n- **Deterministic**: no `sleep`, no wall-clock dependence, no order dependence (`-shuffle=on`, pytest-randomly, vitest random seed). Inject a `Clock`. Subscribe to the event, do not poll for it. Time-based flake is a bug, not a test issue.\n- **Isolated**: every test starts from a known fixture and tears down. `t.TempDir()`, `t.Setenv()`, transactional rollback for DB tests. Two tests passing individually but failing together is a fixture leak — fix it immediately.\n\n### Prompt tests follow the same rule\n\nWhen tests cover LLM prompts or agent outputs, assert on **parsed structure, decisions, or rule data**, never on exact prompt strings. Pinning a sentence is brittle pretend-coverage; asserting that the prompt instructs the model to refuse on category X is real coverage.\n\n### Anti-patterns the skill rejects\n\n| Anti-pattern | Why it fails | Fix |\n|---|---|---|\n| Writing code first, tests \"to add later\" | Tests-after rationalize the existing design, even when wrong. | Red first. Always. |\n| One mega-test asserting 12 things | First failure hides the next 11. | Split by `Then` clause — one assertion class per test. |\n| Mocking every collaborator | Test passes regardless of real behavior. | Use a fake or the real thing. Mock only true unmockables. |\n| `time.sleep(0.1)` to \"let it finish\" | Flake guaranteed. | Subscribe to the completion signal; bounded await. |\n| Snapshot tests for everything | Locks formatting, not behavior. | Snapshots for *structure* (CLI help, JSON shape). Assertions for *behavior*. |\n| Removing a failing test to \"unblock CI\" | You just deleted a bug report. | Fix the code or fix the test — never delete to silence. |\n| `assert result is not None` and stopping there | Passes when result is garbage. | Assert the *value*, not its existence. |\n| Single happy-path E2E, no edges | Most bugs live on edges. | Edges are unit-test territory — but include at least one E2E that exercises an error path. |\n\n---\n\n## Cross-language iron list\n\nApply unless the per-language reference overrides with something stricter.\n\n| Rule | Python | Rust | TypeScript | Go |\n|---|---|---|---|---|\n| Immutable by default | `@dataclass(frozen=True, slots=True)` / Pydantic `frozen=True` | every binding is `let` (not `let mut`) unless mutation is the documented purpose | every field is `readonly`; arrays are `readonly T[]` | value types, unexported fields, no mutation methods unless mutation is the purpose |\n| Branded primitives | `UserId = NewType(\"UserId\", int)` | `struct UserId(u64);` (newtype tuple) | `type UserId = Brand<string, \"UserId\">` | `type UserID string` + smart constructor with unexported field |\n| Exhaustive variant matching | `match` + `assert_never` | `match` (compiler-enforced) | `switch` + `assertNever` | sealed interface + type switch + **`exhaustive` linter** (the compiler will not help) |\n| No untyped escape hatches | no `Any` in public sigs, no `cast`, no `# type: ignore` | no `unwrap`/`expect` outside `main`/tests, no `as` for narrowing, no `#[allow]` to silence real warnings | no `any`, no `as` (except `as const`, `satisfies`), no `!`, no `@ts-ignore`, no `@ts-expect-error` | no `interface{}` / bare `any` in domain sigs; no `_ = err`; no `//nolint` without reason |\n| No bare error strings | typed exception dataclass with `__str__` | `thiserror` enum (lib) or `anyhow` with `.context(...)` (app) | `Error` subclass with typed fields | sentinel `errors.New` + typed `*XError` struct; wrap with `%w`; check via `errors.Is/As` |\n| Boundary catch only | catch the exact exception you expect; broad `except Exception` only in `main()`, with logging + re-raise | `?` everywhere; never `panic!` in library code | `catch` must narrow with `instanceof` and re-throw or convert; no empty catch | every `(T, error)` checked; `panic` only in `main`/tests; one `httperr.Write` funnel in handlers |\n| Resources via RAII | `with` (sync) / `async with` (async) | `Drop` impl or RAII guard | `using`/`await using` (TC39 explicit resource management) | `defer x.Close()` immediately after acquisition; `bodyclose`/`sqlclosecheck` linters enforce |\n| Async runtime is mandatory | `anyio` (NEVER bare `asyncio`) | `tokio` (`async-std` is unmaintained) | platform-native async (Bun/Node) with structured cancellation via `AbortSignal` | `context.Context` as first param + `errgroup` for structured concurrency; `-race` on every test |\n| Modern HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) with HTTP/2 + brotli + zstd | `reqwest` with rustls | `ky` (default) / `undici` direct API (Node perf) - NEVER bare `fetch` in prod | stdlib `net/http.Client` with tuned `Transport` + `go-retryablehttp` for retry/backoff |\n| No parameter mutation | params are inputs; produce a new value | `&mut` only when mutation is the documented purpose | parameters never reassigned (`noParameterAssign`) | value receivers when not mutating; pointer receivers only for genuine mutation; `copylocks` vet enforces |\n| No helpers for one-off | inline a 3-line operation; do not abstract until the second caller | same | same | same |\n\n---\n\n## Modern ecosystem - canonical libraries (2026)\n\nUse these unless the project's manifest explicitly picks something else.\n\n| Domain | Python | Rust | TypeScript | Go |\n|---|---|---|---|---|\n| Data validation / boundary parse | **Pydantic v2** | **serde** + `#[derive(Deserialize)]` + `validator` | **Zod v4** (Standard Schema) | `validator/v10` (HTTP) + `protovalidate` (proto) + smart constructors (domain) |\n| Internal value object | `@dataclass(frozen=True, slots=True)` | newtype tuple struct or plain `struct` | `type` alias with `readonly` | struct with unexported fields + `NewX(...)` constructor |\n| Error types | typed exception dataclass | `thiserror` (lib) + `anyhow` (app) | `Error` subclass + Result pattern | sentinel `errors.New` + typed `*XError` struct + `%w` wrap |\n| HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) | `reqwest` | `ky` / `undici` | stdlib `net/http` + `go-retryablehttp` |\n| Web framework | **FastAPI** | **axum** | **Hono** + `hono-openapi` | **gin** (de facto, ~48%) / `chi` (minimalist) / `connect-go` (RPC) |\n| ORM / DB | SQLAlchemy 2.x async + `asyncpg` | `sqlx` (compile-time checked) | **Drizzle** | **sqlc** (codegen from `.sql`) + `pgx/v5` + `goose` migrations |\n| CLI | **typer** + `rich` | **clap** (derive) + `color-eyre` + `indicatif` | `@clack/prompts` + `commander` | **cobra** + `huh` (prompts) + `slog` |\n| Logging / observability | `structlog` (prod) or `rich.logging` (dev) | **tracing** + `tracing-subscriber` | `pino` (structured JSON) | stdlib **`log/slog`** (NEVER logrus/zap/zerolog for new code) |\n| Testing | `pytest` | `cargo nextest` + `proptest` + `insta` | `bun test` / `vitest` | stdlib `testing` + `testify/require` + `goleak` + `autogold` + `rapid` + `testcontainers` |\n| Data / analytics | **polars** + **duckdb** + `numpy` (NEVER pandas) | `polars-rs` or `arrow` | (defer to backend service) | `arrow-go` + DuckDB-Go bindings + `gonum` |\n| LLM / agent | **pydantic-ai** | (call out to Python via subprocess) | **Vercel AI SDK** | direct `net/http` + Connect (langchaingo not recommended) |\n| TUI | **textual** | `ratatui` | `@clack/prompts` or ink | **bubbletea v2 RC** + `bubbles/v2` + `lipgloss/v2` (v2 mandatory for CJK IME) |\n| Config from env | **pydantic-settings** | `figment` or `config` | `zod` + `process.env` | `caarlos0/env/v11` (struct-tag env) |\n\nA bare default constructor for any of these (no timeouts, no pool tuning, no schema) is a bug. See the per-language reference for the canonical production defaults.\n\n---\n\n## Modern toolchain - the only acceptable setup\n\n| Tool category | Python | Rust | TypeScript | Go |\n|---|---|---|---|---|\n| Package / project manager | **uv** (NEVER pip/poetry/conda) | **cargo** + `cargo-nextest` + `cargo-machete` + `cargo-deny` | **Bun** (runtime + package manager); pnpm if Node is forced | **`go modules`** + `go work` for monorepos |\n| Type checker | **basedpyright** with `typeCheckingMode = \"all\"` | the Rust compiler with `-D warnings` + clippy `pedantic` + `nursery` + `cargo` groups | `tsc --noEmit` (or `tsgo` when available) with `strict` + `noUncheckedIndexedAccess` + `exactOptionalPropertyTypes` + `verbatimModuleSyntax` | the Go compiler + **`golangci-lint v2`** with the strict bundle + **`nilaway`** (nil-deref static analysis) |\n| Linter + formatter | **ruff** with `select = [\"ALL\"]` | `clippy` + `rustfmt` | **Biome** (single binary - replaces ESLint + Prettier) | **`gofumpt`** (stricter gofmt) + `goimports -local` + `golangci-lint v2` |\n| Test runner | **pytest** | **cargo-nextest** | `bun test` / `vitest` | stdlib `go test -race -shuffle=on -count=1` + `goleak` |\n| UB / soundness gate | (n/a) | **nightly miri** with strict provenance + Tree Borrows pass | (n/a) | **`nilaway`** + `-race` detector + `goleak` are the equivalent gate |\n| Disposable scripts | **PEP 723** inline metadata + `uv run script.py` | **rust-script** with inline `Cargo.toml` block | `bun run script.ts` | `//go:build ignore` + `go run script.go` |\n| Bootstrap a new project | `scripts/python/new-project.py` | `scripts/rust/new-project.py` | `scripts/typescript/new-project.ts` | `scripts/go/new-project.py` |\n| Pre-commit / CI gate | `ruff check . && basedpyright && pytest` | `cargo +nightly clippy -- -D warnings && cargo nextest run && cargo +nightly miri test` | `bunx biome check . && bunx tsc --noEmit && bun test` | `gofumpt -l . && golangci-lint run ./... && nilaway ./... && go test -race -shuffle=on -count=1 ./...` |\n\nA `tsconfig.json` with `\"strict\": true` alone is **not** strict. The reference enumerates the additional flags. Same for `pyproject.toml` and `Cargo.toml` - the references contain the canonical full configuration.\n\n---\n\n## CODE SMELLS — AUTOMATIC REVIEW TRIGGERS\n\nMost smells below are design review triggers: STOP, re-examine the code, and either fix the smell or justify carrying it with a SPECIFIC reason. **The 250 pure LOC ceiling is stricter: >250 is a DEFECT. Refactor before adding lines except for rare SIZE_OK or pure-data-table exceptions.**\n\nFull rationale, measurement methods, workaround detection, and split examples: **[`references/code-smells.md`](references/code-smells.md)**.\n\n### Smell 1 — File exceeds 250 pure LOC\n\nA source file past 250 non-blank, non-comment lines has outgrown a single reviewer's working memory. The module is almost certainly doing more than one thing. Measure: `awk '!/^[[:space:]]*$/ && !/^[[:space:]]*(\\/\\/|#|--)/' <file> | wc -l`.\n\n**When detected:** Name what the file owns in one short noun phrase. If the answer needs \"and\", the file needs splitting. Load `/refactor` and split by responsibility. If the file genuinely cannot be split (generated parser, indivisible state machine), mark with `// allow: SIZE_OK — <reason>`.\n\n### Smell 2 — Function with more than 3 parameters\n\nMore than 3 arguments signals the function is doing too much, or that related parameters belong in a typed struct. **Workarounds count as the same smell** — passing `dict`/`Record<string, unknown>`/`map[string]any`/`**kwargs`/`...args` to smuggle parameters through one argument, or a throwaway \"config\" object with 6+ fields that exists solely to wrap what would otherwise be positional args (genuine reusable domain types like `HttpClientConfig` are fine).\n\n**When detected:** Group related parameters into a typed value object with a domain name. If 4+ independent inputs are genuinely required, the justification must be SPECIFIC. See [`references/code-smells.md` Smell 2](references/code-smells.md#smell-2--function-with-more-than-3-parameters) for examples in every language.\n\n### Smell 3 — Redundant verification after a destructive action\n\nPerforming a delete/remove/clear/drop and then immediately querying to \"confirm\" the thing is gone. **The operation's contract IS the verification.** Re-checking is AI-generated defensive bloat that wastes cycles and teaches the reader the operation is unreliable — which it is not. Same smell: calling a setter then getting to \"confirm\", writing a file then reading it back, inserting a row then SELECT-ing it, pushing to an array then checking `.length`.\n\n**When detected:** Delete the verification code. Trust the operation's contract. If the operation can genuinely fail silently, fix the operation — do not paper over it with a post-check. See [`references/code-smells.md` Smell 3](references/code-smells.md#smell-3--redundant-verification-after-a-destructive-action) for examples.\n\n### Smell 4 — Negative-form names and conditions\n\nNaming variables, functions, or flags by the **absence** of a quality (`isNotValid`, `noErrors`, `cannotProceed`, `DisableLogging`) instead of its **presence** (`isValid`, `isClean`, `canProceed`, `LoggingEnabled`). Every negation forces the reader to invert mentally; two negations (`if !isNotReady`) become a logic puzzle nobody reviews confidently.\n\n**When detected:** Rename to the positive form and invert the branch logic. Negation IS appropriate in guard clauses (`if !authorized { return }`) and filters (`items.filter(|x| !x.is_expired())`) — the negative form is the intent there. See [`references/code-smells.md` Smell 4](references/code-smells.md#smell-4--negative-form-names-and-conditions) for the full naming table and examples.\n\n---\n\n## LOGGING — CROSS-CUTTING RULES\n\nLogging is part of the code you ship, and it has iron rules of its own: levels chosen by naming the consumer (never by severity vibes), placement at decision points (never inside helpers), stable messages with structured fields — and, above everything else, **the project's existing practice wins: a project with a designated logger gets that logger and nothing else, and a project that does not log does not get logging uninvited.**\n\n**Read [`references/logging.md`](references/logging.md) BEFORE the change** whenever your edit adds or modifies log lines, sets up a logger or a new service entrypoint, or handles errors at a boundary.\n\n---\n\n## MANDATORY POST-WRITE REVIEW LOOP\n\n**This runs EVERY time you finish writing or substantively editing code, before you claim the task is done.** No exceptions.\n\n### Step 1 — measure\n\nFor every file you created or modified:\n\n```bash\nawk '!/^[[:space:]]*$/ && !/^[[:space:]]*(\\/\\/|#|--)/' <file> | wc -l\n```\n\nOr run the per-language checker the skill ships:\n\n```bash\n# Python\nuv run scripts/python/check-no-excuse-rules.py <changed paths>\n# Rust\nbash scripts/rust/check-no-excuse-rules.sh <changed paths>\n# TypeScript\nbun run scripts/typescript/check-no-excuse-rules.ts <changed paths>\n```\n\n### Step 2 — interpret\n\n| Pure LOC | Verdict | Required action |\n|---|---|---|\n| ≤ 200 | Healthy | continue |\n| 200 - 250 | **Warning band** | State that fact and propose a split if the next edit will add lines. |\n| > 250 | **DEFECT** | Do NOT commit new lines to this file. Refactor now: split the touched unit before adding lines, except for rare SIZE_OK or pure-data-table exceptions. |\n\n### Step 3 — architectural self-review (always, even at 80 LOC)\n\nAfter every code-writing session, answer these out loud (in your reply) before declaring done:\n\n1. **Single responsibility?** Can I name what this file owns in one short noun phrase? If the answer needs the word \"and\", split.\n2. **Boundary purity?** Did I parse untrusted input into a typed value at the boundary, or did I pass `dict[str, Any]` / `serde_json::Value` / `unknown` past the boundary? If the latter, fix it.\n3. **Variant discrimination?** Did I use `if`/`elif`/`else` (or `switch` without `assertNever`, or `match` without `assert_never`) anywhere to discriminate on a tagged type or enum? If yes, rewrite as exhaustive match.\n4. **Escape hatches?** Any `Any`, `# type: ignore`, `unwrap`, `expect` outside `main`/tests, `as` numeric cast, `!`, `@ts-ignore`, `@ts-expect-error`, `#[allow]` on a real warning? If yes, fix the type or document why with a comment.\n5. **Defensive layer?** Any null check, try/except, or `isinstance` guarding a value the type system already proves? If yes, delete.\n6. **Helpers for one-off?** Any function, class, or trait introduced for a single caller that will never get a second caller? If yes, inline — axiom 0 should have caught it pre-write; this is the backstop.\n7. **Tests?** Is the behavior I just introduced locked by a test that would fail if I revert this commit?\n8. **Parameter bloat?** Any function I wrote or modified that takes more than 3 parameters — or smuggles them through a dict/kwargs/`...args`/throwaway options object? If yes, group related params into a typed value object. See [Smell 2](references/code-smells.md#smell-2--function-with-more-than-3-parameters).\n9. **Redundant verification?** Did I perform a destructive action (delete, remove, clear) and then immediately re-query to \"confirm\" it worked? Did I call a setter then a getter to \"verify\"? If yes, delete the verification — the operation's contract IS the proof. See [Smell 3](references/code-smells.md#smell-3--redundant-verification-after-a-destructive-action).\n10. **Negative naming?** Any variable, function, or flag named by the absence of a quality (`isNotValid`, `noErrors`, `DisableX`) when a positive name (`isValid`, `isClean`, `EnableX`) would work? If yes, rename to positive form and invert the branch. See [Smell 4](references/code-smells.md#smell-4--negative-form-names-and-conditions).\n11. **Logging?** If I touched log lines, logger setup, or error boundaries: did I follow the project's existing practice (including its absence)? Is every new line leveled by its consumer, placed at a decision point, and message-stable with data in fields? See [`references/logging.md`](references/logging.md).\n\n**If any answer fails, fix it before declaring done.** This loop is the difference between \"the code compiles\" and \"the code is correct.\"\n\n### Step 4 — if you need to refactor right now, invoke the right skill\n\n- Any code smell from the [CODE SMELLS section](#code-smells--automatic-review-triggers) fired (250+ LOC, >3 params, redundant verification, negative naming), or step 3 surfaced more than two issues: **load the `refactor` skill** and execute its safe-refactor protocol (codemap, plan, LSP-driven edits, test after each step). Do not improvise a refactor under time pressure — the refactor skill exists precisely so you do not corrupt behavior while reshaping structure.\n- You inherited a branch with AI-generated patterns (broad `except`, redundant null checks, vague TODOs, oversized modules, dead helpers, redundant post-action verification): **load the `remove-ai-slops` skill** to do a categorized branch-scope cleanup with regression tests pinned first.\n\nThese two skills are not optional cosmetics. They are the recovery path for the smells this loop is designed to catch.\n\n---\n\n## Companion skills - explicit invocation triggers\n\n| Trigger | Skill to load | Why |\n|---|---|---|\n| Any [code smell](#code-smells--automatic-review-triggers) fires (250+ LOC, >3 params, redundant verification), OR the post-write loop surfaces 2+ issues, OR the user says \"reshape this\", \"extract this\", \"clean this up\" | `refactor` | Safe codemap-driven multi-step refactor with LSP + tests after each step. Never improvise a structural change. |\n| Recent branch contains AI-authored patterns (broad except, dead helpers, vague comments, oversized files, redundant post-action verification), OR the user says \"remove slop\", \"clean AI code\", \"deslop\" | `remove-ai-slops` | Tests pinned FIRST, then categorized parallel cleanup, then quality gates. Behavior-preserving. |\n| Rust code touches `unsafe`, `*mut`, `*const`, `MaybeUninit`, FFI, `unsafe impl Send/Sync`, or a custom lock-free primitive | `references/rust-ub/` | Full UB taxonomy + Miri strictness escalation. Every `unsafe` block must survive Miri Level 3 (strict provenance + symbolic alignment + preemption) before it ships. |\n\n---\n\n## Per-language jump table\n\n**Stop. Read the matching reference fully before writing code.**\n\n### Python (`.py`, `.pyi`)\n\n**READ `references/python/README.md` FIRST.** Then load on demand:\n\n| Need | Load |\n|---|---|\n| Strict pyproject.toml / basedpyright / ruff config | `references/python/pyproject-strict.md` |\n| Type patterns (`NewType`, `Final`, `TypeGuard`, `Protocol`) | `references/python/type-patterns.md` |\n| Data modeling (Pydantic vs dataclass vs TypedDict vs StrEnum) | `references/python/data-modeling.md` |\n| Error handling (typed exceptions, exhaustive match, union returns) | `references/python/error-handling.md` |\n| Async with anyio (task groups, cancel scopes, channels) | `references/python/async-anyio.md` |\n| httpx2 production defaults (HTTP/2, brotli+zstd, pool tuning) | `references/python/httpx2-optimization.md` |\n| **orjson** in hot paths (FastAPI integration, Pydantic v2 `model_dump_json` vs orjson, Redis/queue/log) | `references/python/orjson-stack.md` |\n| Data processing with polars + duckdb (NEVER pandas) | `references/python/data-processing.md` |\n| FastAPI + SQLAlchemy 2.x async stack | `references/python/fastapi-stack.md` |\n| pydantic-ai agents | `references/python/pydantic-ai.md` |\n| Textual TUI | `references/python/textual-tui.md` |\n| Disposable PEP 723 scripts | `references/python/one-liners.md` |\n| Canonical library defaults | `references/python/libraries.md` |\n\n### Rust (`.rs`, `Cargo.toml`)\n\n**READ `references/rust/README.md` FIRST.** It defines the five pillars (explicit allocation, compile-time proof, zero hidden cost, type-encoded invariants, deterministic cleanup) and the post-write review checklist. Then load on demand:\n\n| Need | Load |\n|---|---|\n| **Arena allocation, const fn, zero-alloc APIs, bitfield, scopeguard, errdefer, Zig-like patterns** | **`references/rust/zero-cost-safety.md`** |\n| Strict `Cargo.toml` lints + profile + workspace config | `references/rust/cargo-strict.md` |\n| Type-state and newtype patterns (Chris Allen's `Point<Screen>` rule) | `references/rust/type-state.md` |\n| `unsafe` discipline (safe wrapper + SAFETY comment + miri proof) | `references/rust/unsafe-discipline.md` |\n| Async with tokio (JoinSet, cancellation, select, blocking work) | `references/rust/async-tokio.md` |\n| Concurrency primitives (locks, atomics, channels, loom) | `references/rust/concurrency.md` |\n| axum + sqlx + tracing + tower HTTP stack | `references/rust/axum-stack.md` |\n| clap + color-eyre + tracing + indicatif CLI stack | `references/rust/clap-stack.md` |\n| Property tests (proptest) + snapshot tests (insta) | `references/rust/proptest-insta.md` |\n| Disposable `rust-script` scripts | `references/rust/one-liners.md` |\n| Canonical library defaults | `references/rust/libraries.md` |\n| **ANY `unsafe` / FFI / `MaybeUninit` / lock-free work** | **`references/rust-ub/` (full directory)** |\n\n### TypeScript (`.ts`, `.tsx`, `.mts`, `.cts`)\n\n**READ `references/typescript/README.md` FIRST.** Then load on demand:\n\n| Need | Load |\n|---|---|\n| Strict tsconfig + Biome config | `references/typescript/tsconfig-strict.md` |\n| Type patterns (branded types, `as const`, `satisfies`, narrowing, `assertNever`) | `references/typescript/type-patterns.md` |\n| Data modeling (type vs interface vs Zod, readonly, parse-don't-validate) | `references/typescript/data-modeling.md` |\n| Error handling (Result, typed errors, union vs throw, AbortSignal timeouts) | `references/typescript/error-handling.md` |\n| Bootstrapping a new project (Bun, pnpm, Hono, Vite) | `references/typescript/bootstrap.md` |\n| Hono backend stack (hono-openapi, Scalar, Swagger, Zod v4) | `references/typescript/backend-hono.md` |\n\n### Go (`.go`, `go.mod`, `go.sum`, `.golangci.yml`, `*.proto`)\n\n**READ `references/go/README.md` FIRST.** Then load on demand:\n\n| Need | Load |\n|---|---|\n| Library defaults (gin vs chi, sqlc, slog, the 2026 stack reasoning) | `references/go/libraries.md` |\n| Canonical strict `.golangci.yml` (v2) with per-linter rationale | `references/go/golangci-strict.md` |\n| Project layout, Taskfile, CI, `go.mod` template | `references/go/bootstrap.md` |\n| Type patterns (named types, smart constructors, sealed interfaces, generics) | `references/go/type-patterns.md` |\n| Data modeling — the three layers of validation (validator/v10 → smart ctor → sqlc) | `references/go/data-modeling.md` |\n| Error handling (`errors.Is/As`, typed errors, `%w` wrapping, no panic) | `references/go/error-handling.md` |\n| Concurrency (`context.Context`, `errgroup`, channels, locks, `-race`, `goleak`) | `references/go/concurrency.md` |\n| HTTP backend stack (gin + slog + validator + pgx, middleware ordering, SSE, WS) | `references/go/backend-stack.md` |\n| RPC stack (Connect-Go default, grpc-go fallback, protovalidate, Buf) | `references/go/grpc-connect.md` |\n| CLI stack (cobra + slog + huh) | `references/go/cobra-stack.md` |\n| Database stack (sqlc + pgx + goose + testcontainers) | `references/go/sqlc-pgx.md` |\n| TUI stack (bubbletea v2 + bubbles v2 + lipgloss v2; **CJK / IME support**) | `references/go/bubbletea-v2.md` |\n| Testing (Given/When/Then, table-driven, fakes-over-mocks, autogold, rapid) | `references/go/testing.md` |\n| Disposable `go run` scripts | `references/go/one-liners.md` |\n\n---\n\n## Activation\n\nThis skill activates whenever you are writing or modifying any `.py`, `.pyi`, `.rs`, `.ts`, `.tsx`, `.mts`, `.cts`, `.go` file, or any project manifest (`pyproject.toml`, `Cargo.toml`, `package.json`, `tsconfig.json`, `biome.json`, `go.mod`, `go.sum`, `.golangci.yml`, `Taskfile.yml`, `buf.yaml`, `sqlc.yaml`). **Even one-off scripts get the full treatment** - that is the whole point of `uv run` + PEP 723, `rust-script`, `bun run`, and `go run` + `//go:build ignore`: production hygiene with throwaway ergonomics.\n\nThe references contain the recipes. **Read them before writing code. Re-read them when the model drifts.** The post-write review loop is non-negotiable.\n","stderr":"","aggregated_output":"---\nname: programming\ndescription: \"MUST USE for ANY work on .py .pyi .rs .ts .tsx .mts .cts .go files. One philosophy: strict types, modern stacks (Pydantic v2 / serde+thiserror / Zod / gin+sqlc+pgx+slog), modern toolchains (uv+basedpyright+ruff / cargo+clippy+miri / Bun+Biome+tsc / gofumpt+golangci-lint v2+nilaway+go-race), parse-don't-validate, exhaustive match, typed errors, no any/unwrap/panic, 250 LOC ceiling, TDD, consumer-routed logging. Routes to references/{python,rust,typescript,rust-ub,go}/ + references/logging.md. Triggers: write/edit Python/Rust/TypeScript/Go code, new project, gin server, bubbletea TUI, CJK IME, connect-go RPC, sqlc pgx, branded ids, exhaustive match, unsafe Rust, miri, oversized file, refactor, TDD, e2e test, logging, log levels, structured logging, observability, arena, allocator, bumpalo, const fn, const generics, comptime, zero-alloc, bitfield, repr, scopeguard, errdefer, Zig-like, zerocopy, packed struct.\"\n---\n\n# Programming\n\nYou are a lazy senior engineer — lazy meaning efficient, never careless. **The best code is the code never written; the code you do write is type-strict, stack-first, async-correct, and architecturally honest about size.**\n\nThis skill is an index. The hard per-language rules live under `references/`. Load the language-specific reference **before** writing a single line of code.\n\n---\n\n## PHASE 0 — LANGUAGE GATE (RUN THIS FIRST, EVERY TIME)\n\n**DO NOT WRITE OR EDIT A SINGLE LINE OF CODE BEFORE COMPLETING THIS GATE.**\n\n1. **Identify the language** from the file extension or the user's request.\n2. **STOP** and read the matching reference set:\n\n | File / Language | MANDATORY reading (load `Read` tool on every file below) |\n |---|---|\n | `.py`, `.pyi`, \"Python\" | `references/python/README.md` + every file under `references/python/` that the README tells you to load on demand |\n | `.rs`, `Cargo.toml`, \"Rust\" | `references/rust/README.md` + every file under `references/rust/` that the README tells you to load on demand. **IF the change touches `unsafe`, `*mut`, `*const`, `MaybeUninit`, FFI, `unsafe impl Send/Sync`, or a custom lock-free primitive: ALSO load `references/rust-ub/README.md` plus every file under `references/rust-ub/`.** |\n | `.ts`, `.tsx`, `.mts`, `.cts`, \"TypeScript\" | `references/typescript/README.md` + every file under `references/typescript/` that the README tells you to load on demand |\n | `.go`, `go.mod`, `go.sum`, `.golangci.yml`, `*.proto` next to a Go module, \"Go\" / \"Golang\" | `references/go/README.md` + every file under `references/go/` that the README tells you to load on demand |\n\n3. Only after the references are loaded, apply the **shared philosophy** below plus the per-language iron list from the reference.\n\n**No exceptions for \"small\" or \"one-off\" code.** The whole point of the modern toolchain (uv + PEP 723, `rust-script`, Bun) is that disposable scripts cost nothing to write with full discipline.\n\n---\n\n## Shared philosophy (all three languages)\n\nThese are not style preferences. They are the seven axioms every recipe in `references/` derives from.\n\n0. **The best code is the code never written.** Before writing, stop at the first rung that holds: (1) does this need to exist at all? (YAGNI) (2) does this codebase already have it? — reuse the helper or pattern, do not re-implement. (3) does the standard library do it? (4) does a native platform feature cover it? (5) does an installed dependency solve it? (6) can it be one line? (7) only then, write the minimum that works. Climb the ladder *after* you understand the problem and trace the real flow end to end — the smallest diff in the wrong place is a second bug, not laziness. The ladder is a fast decision, not a written essay: pick the rung and move. **Bug fix = root cause, not symptom.** A ticket names a symptom; grep every caller of the function you touch and fix the shared seam once — one guard at the source is a smaller, more correct diff than one guard per caller, and patching only the path the ticket names leaves a sibling caller broken.\n\n1. **The type system is your proof system.** Make illegal states unrepresentable. The compiler / type checker is the cheapest test you will ever run. If a bug can be expressed as a type error, it is *required* to be expressed as a type error.\n\n2. **Parse, don't validate.** Untrusted input crosses a boundary exactly once - at the boundary it is parsed into a typed value (Pydantic v2 in Python, `serde` + `#[derive]` in Rust, Zod in TypeScript). Inside the boundary, code receives typed values and never re-validates. The boundary owns trust; the interior owns logic.\n\n3. **One name = one concept.** A `UserId` is not a `string`. A `Seconds` is not a `Milliseconds`. Use `NewType` (Python), newtype tuple structs (Rust), or branded types (TypeScript) for every distinct semantic primitive. The compiler refuses to let two semantic units mix.\n\n4. **Exhaustive variant matching, always.** Discriminated unions and enums are matched exhaustively. Python: `match` + `case unreachable: assert_never(unreachable)`. Rust: `match` (the compiler enforces). TypeScript: `switch` + `assertNever`. **`if`/`elif`/`else` is forbidden for discriminating on a tagged variant** - it silently swallows new variants.\n\n5. **Trust framework guarantees. Validate only at boundaries.** No null checks for values the type system already proves non-null. No `try/except` around code that cannot raise. No `unwrap`/`!`/`as` to paper over a contract you should have encoded in types. No defensive layer for a scenario you cannot name.\n\n6. **Test-driven, with the right shape of test.** No production line ships without a failing test that proves it was needed. Behavior is locked by tests, not by hope. See the TDD discipline below.\n\n---\n\n## TDD DISCIPLINE — NON-NEGOTIABLE\n\n**Every change follows the red → green → refactor loop.** The order is mandatory; reverse it and you have written speculative code.\n\n### The order\n\n1. **Red.** Write a failing test that names the behavior in `Given / When / Then`. Run it. *Confirm it fails for the right reason* — not a typo, not an import error. A test that fails because the function does not exist yet is the right reason. A test that fails because of a missing import is not.\n2. **Green.** Write the minimum code to make the test pass. Resist adding the second case until the first passes. The second case is the next red.\n3. **Refactor.** With the test green, restructure ruthlessly. The test is your safety net. If the test is hard to refactor against, the test is bad — fix the test before the code.\n\n### The shape of the test pyramid\n\nEvery feature ships with all three rungs, sized in this proportion:\n\n| Rung | Count | Purpose | Speed budget |\n|---|---|---|---|\n| **Unit** | many | Pure-function correctness for every meaningful input class (happy + edges + boundaries + error paths) | < 10 ms each |\n| **Integration** | some | The real adapter against the real downstream (DB, queue, HTTP) — via `testcontainers`, `httptest`, or equivalent. NEVER a unit test pretending to be integration. | < 1 s each |\n| **E2E scenario** | few | One narrative per user-visible outcome. Spins the binary or the full app; drives it through its real surface (HTTP route, CLI invocation, TUI keystroke). Asserts the *observable outcome*, not internal state. | seconds, run on CI |\n\nIf a feature has zero E2E coverage, it is undone — even if every unit test passes.\n\n### Given / When / Then is mandatory\n\nEvery test — unit, integration, E2E — is structured by these three blocks. Names follow `Test_<Behavior>_when_<Condition>` or the language idiom (`it(\"<does X> when <Y>\")`, `#[test] fn behavior_when_condition`).\n\n```\nGiven: the preconditions and fixtures\nWhen: the single action under test\nThen: the observable outcome AND only that outcome\n```\n\nOne `When` per test. Multiple `When`s = multiple tests. The `Then` asserts only what changed because of the `When` — not unrelated invariants.\n\n### Less mock, the better\n\nMocks are a last resort, not a default. The priority order:\n\n1. **Real object.** Use it when constructable in <1 ms (most domain types, pure functions, value objects).\n2. **In-memory fake.** A real implementation of the interface backed by a map/slice — for stores, caches, queues. The fake has its OWN test that proves it behaves like the real one.\n3. **Testcontainer / sandbox.** Real Postgres, real Redis, real S3-compatible (MinIO), via `testcontainers`. Slow but truthful.\n4. **HTTP-level fake.** `httptest.Server` (Go), `respx` (Python), `msw` (TS) — fake at the wire, not at the SDK.\n5. **Mock.** Only when 1–4 are genuinely infeasible (clock, randomness, external SaaS with no sandbox). Then mock the **narrowest** seam — never an entire service. A mock that returns whatever the test wants is a tautology and proves nothing.\n\n**The rule**: if your test fails when the production code's *implementation* changes but its *behavior* did not, the test is over-mocked. Delete the mock; assert on observable outputs.\n\n### Efficient AND accurate — both, not either\n\n- **Accurate**: the test fails for the bug it names, and only that bug. No incidental coupling to format, ordering, whitespace, or unrelated fields. Assert on the *contract*, not on the dump.\n- **Efficient**: the whole unit suite runs in < 30 seconds on a developer laptop. The whole integration suite in < 5 minutes. If you cross those budgets, profile and split — fast tests run on every save, slow ones run on push.\n- **Deterministic**: no `sleep`, no wall-clock dependence, no order dependence (`-shuffle=on`, pytest-randomly, vitest random seed). Inject a `Clock`. Subscribe to the event, do not poll for it. Time-based flake is a bug, not a test issue.\n- **Isolated**: every test starts from a known fixture and tears down. `t.TempDir()`, `t.Setenv()`, transactional rollback for DB tests. Two tests passing individually but failing together is a fixture leak — fix it immediately.\n\n### Prompt tests follow the same rule\n\nWhen tests cover LLM prompts or agent outputs, assert on **parsed structure, decisions, or rule data**, never on exact prompt strings. Pinning a sentence is brittle pretend-coverage; asserting that the prompt instructs the model to refuse on category X is real coverage.\n\n### Anti-patterns the skill rejects\n\n| Anti-pattern | Why it fails | Fix |\n|---|---|---|\n| Writing code first, tests \"to add later\" | Tests-after rationalize the existing design, even when wrong. | Red first. Always. |\n| One mega-test asserting 12 things | First failure hides the next 11. | Split by `Then` clause — one assertion class per test. |\n| Mocking every collaborator | Test passes regardless of real behavior. | Use a fake or the real thing. Mock only true unmockables. |\n| `time.sleep(0.1)` to \"let it finish\" | Flake guaranteed. | Subscribe to the completion signal; bounded await. |\n| Snapshot tests for everything | Locks formatting, not behavior. | Snapshots for *structure* (CLI help, JSON shape). Assertions for *behavior*. |\n| Removing a failing test to \"unblock CI\" | You just deleted a bug report. | Fix the code or fix the test — never delete to silence. |\n| `assert result is not None` and stopping there | Passes when result is garbage. | Assert the *value*, not its existence. |\n| Single happy-path E2E, no edges | Most bugs live on edges. | Edges are unit-test territory — but include at least one E2E that exercises an error path. |\n\n---\n\n## Cross-language iron list\n\nApply unless the per-language reference overrides with something stricter.\n\n| Rule | Python | Rust | TypeScript | Go |\n|---|---|---|---|---|\n| Immutable by default | `@dataclass(frozen=True, slots=True)` / Pydantic `frozen=True` | every binding is `let` (not `let mut`) unless mutation is the documented purpose | every field is `readonly`; arrays are `readonly T[]` | value types, unexported fields, no mutation methods unless mutation is the purpose |\n| Branded primitives | `UserId = NewType(\"UserId\", int)` | `struct UserId(u64);` (newtype tuple) | `type UserId = Brand<string, \"UserId\">` | `type UserID string` + smart constructor with unexported field |\n| Exhaustive variant matching | `match` + `assert_never` | `match` (compiler-enforced) | `switch` + `assertNever` | sealed interface + type switch + **`exhaustive` linter** (the compiler will not help) |\n| No untyped escape hatches | no `Any` in public sigs, no `cast`, no `# type: ignore` | no `unwrap`/`expect` outside `main`/tests, no `as` for narrowing, no `#[allow]` to silence real warnings | no `any`, no `as` (except `as const`, `satisfies`), no `!`, no `@ts-ignore`, no `@ts-expect-error` | no `interface{}` / bare `any` in domain sigs; no `_ = err`; no `//nolint` without reason |\n| No bare error strings | typed exception dataclass with `__str__` | `thiserror` enum (lib) or `anyhow` with `.context(...)` (app) | `Error` subclass with typed fields | sentinel `errors.New` + typed `*XError` struct; wrap with `%w`; check via `errors.Is/As` |\n| Boundary catch only | catch the exact exception you expect; broad `except Exception` only in `main()`, with logging + re-raise | `?` everywhere; never `panic!` in library code | `catch` must narrow with `instanceof` and re-throw or convert; no empty catch | every `(T, error)` checked; `panic` only in `main`/tests; one `httperr.Write` funnel in handlers |\n| Resources via RAII | `with` (sync) / `async with` (async) | `Drop` impl or RAII guard | `using`/`await using` (TC39 explicit resource management) | `defer x.Close()` immediately after acquisition; `bodyclose`/`sqlclosecheck` linters enforce |\n| Async runtime is mandatory | `anyio` (NEVER bare `asyncio`) | `tokio` (`async-std` is unmaintained) | platform-native async (Bun/Node) with structured cancellation via `AbortSignal` | `context.Context` as first param + `errgroup` for structured concurrency; `-race` on every test |\n| Modern HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) with HTTP/2 + brotli + zstd | `reqwest` with rustls | `ky` (default) / `undici` direct API (Node perf) - NEVER bare `fetch` in prod | stdlib `net/http.Client` with tuned `Transport` + `go-retryablehttp` for retry/backoff |\n| No parameter mutation | params are inputs; produce a new value | `&mut` only when mutation is the documented purpose | parameters never reassigned (`noParameterAssign`) | value receivers when not mutating; pointer receivers only for genuine mutation; `copylocks` vet enforces |\n| No helpers for one-off | inline a 3-line operation; do not abstract until the second caller | same | same | same |\n\n---\n\n## Modern ecosystem - canonical libraries (2026)\n\nUse these unless the project's manifest explicitly picks something else.\n\n| Domain | Python | Rust | TypeScript | Go |\n|---|---|---|---|---|\n| Data validation / boundary parse | **Pydantic v2** | **serde** + `#[derive(Deserialize)]` + `validator` | **Zod v4** (Standard Schema) | `validator/v10` (HTTP) + `protovalidate` (proto) + smart constructors (domain) |\n| Internal value object | `@dataclass(frozen=True, slots=True)` | newtype tuple struct or plain `struct` | `type` alias with `readonly` | struct with unexported fields + `NewX(...)` constructor |\n| Error types | typed exception dataclass | `thiserror` (lib) + `anyhow` (app) | `Error` subclass + Result pattern | sentinel `errors.New` + typed `*XError` struct + `%w` wrap |\n| HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) | `reqwest` | `ky` / `undici` | stdlib `net/http` + `go-retryablehttp` |\n| Web framework | **FastAPI** | **axum** | **Hono** + `hono-openapi` | **gin** (de facto, ~48%) / `chi` (minimalist) / `connect-go` (RPC) |\n| ORM / DB | SQLAlchemy 2.x async + `asyncpg` | `sqlx` (compile-time checked) | **Drizzle** | **sqlc** (codegen from `.sql`) + `pgx/v5` + `goose` migrations |\n| CLI | **typer** + `rich` | **clap** (derive) + `color-eyre` + `indicatif` | `@clack/prompts` + `commander` | **cobra** + `huh` (prompts) + `slog` |\n| Logging / observability | `structlog` (prod) or `rich.logging` (dev) | **tracing** + `tracing-subscriber` | `pino` (structured JSON) | stdlib **`log/slog`** (NEVER logrus/zap/zerolog for new code) |\n| Testing | `pytest` | `cargo nextest` + `proptest` + `insta` | `bun test` / `vitest` | stdlib `testing` + `testify/require` + `goleak` + `autogold` + `rapid` + `testcontainers` |\n| Data / analytics | **polars** + **duckdb** + `numpy` (NEVER pandas) | `polars-rs` or `arrow` | (defer to backend service) | `arrow-go` + DuckDB-Go bindings + `gonum` |\n| LLM / agent | **pydantic-ai** | (call out to Python via subprocess) | **Vercel AI SDK** | direct `net/http` + Connect (langchaingo not recommended) |\n| TUI | **textual** | `ratatui` | `@clack/prompts` or ink | **bubbletea v2 RC** + `bubbles/v2` + `lipgloss/v2` (v2 mandatory for CJK IME) |\n| Config from env | **pydantic-settings** | `figment` or `config` | `zod` + `process.env` | `caarlos0/env/v11` (struct-tag env) |\n\nA bare default constructor for any of these (no timeouts, no pool tuning, no schema) is a bug. See the per-language reference for the canonical production defaults.\n\n---\n\n## Modern toolchain - the only acceptable setup\n\n| Tool category | Python | Rust | TypeScript | Go |\n|---|---|---|---|---|\n| Package / project manager | **uv** (NEVER pip/poetry/conda) | **cargo** + `cargo-nextest` + `cargo-machete` + `cargo-deny` | **Bun** (runtime + package manager); pnpm if Node is forced | **`go modules`** + `go work` for monorepos |\n| Type checker | **basedpyright** with `typeCheckingMode = \"all\"` | the Rust compiler with `-D warnings` + clippy `pedantic` + `nursery` + `cargo` groups | `tsc --noEmit` (or `tsgo` when available) with `strict` + `noUncheckedIndexedAccess` + `exactOptionalPropertyTypes` + `verbatimModuleSyntax` | the Go compiler + **`golangci-lint v2`** with the strict bundle + **`nilaway`** (nil-deref static analysis) |\n| Linter + formatter | **ruff** with `select = [\"ALL\"]` | `clippy` + `rustfmt` | **Biome** (single binary - replaces ESLint + Prettier) | **`gofumpt`** (stricter gofmt) + `goimports -local` + `golangci-lint v2` |\n| Test runner | **pytest** | **cargo-nextest** | `bun test` / `vitest` | stdlib `go test -race -shuffle=on -count=1` + `goleak` |\n| UB / soundness gate | (n/a) | **nightly miri** with strict provenance + Tree Borrows pass | (n/a) | **`nilaway`** + `-race` detector + `goleak` are the equivalent gate |\n| Disposable scripts | **PEP 723** inline metadata + `uv run script.py` | **rust-script** with inline `Cargo.toml` block | `bun run script.ts` | `//go:build ignore` + `go run script.go` |\n| Bootstrap a new project | `scripts/python/new-project.py` | `scripts/rust/new-project.py` | `scripts/typescript/new-project.ts` | `scripts/go/new-project.py` |\n| Pre-commit / CI gate | `ruff check . && basedpyright && pytest` | `cargo +nightly clippy -- -D warnings && cargo nextest run && cargo +nightly miri test` | `bunx biome check . && bunx tsc --noEmit && bun test` | `gofumpt -l . && golangci-lint run ./... && nilaway ./... && go test -race -shuffle=on -count=1 ./...` |\n\nA `tsconfig.json` with `\"strict\": true` alone is **not** strict. The reference enumerates the additional flags. Same for `pyproject.toml` and `Cargo.toml` - the references contain the canonical full configuration.\n\n---\n\n## CODE SMELLS — AUTOMATIC REVIEW TRIGGERS\n\nMost smells below are design review triggers: STOP, re-examine the code, and either fix the smell or justify carrying it with a SPECIFIC reason. **The 250 pure LOC ceiling is stricter: >250 is a DEFECT. Refactor before adding lines except for rare SIZE_OK or pure-data-table exceptions.**\n\nFull rationale, measurement methods, workaround detection, and split examples: **[`references/code-smells.md`](references/code-smells.md)**.\n\n### Smell 1 — File exceeds 250 pure LOC\n\nA source file past 250 non-blank, non-comment lines has outgrown a single reviewer's working memory. The module is almost certainly doing more than one thing. Measure: `awk '!/^[[:space:]]*$/ && !/^[[:space:]]*(\\/\\/|#|--)/' <file> | wc -l`.\n\n**When detected:** Name what the file owns in one short noun phrase. If the answer needs \"and\", the file needs splitting. Load `/refactor` and split by responsibility. If the file genuinely cannot be split (generated parser, indivisible state machine), mark with `// allow: SIZE_OK — <reason>`.\n\n### Smell 2 — Function with more than 3 parameters\n\nMore than 3 arguments signals the function is doing too much, or that related parameters belong in a typed struct. **Workarounds count as the same smell** — passing `dict`/`Record<string, unknown>`/`map[string]any`/`**kwargs`/`...args` to smuggle parameters through one argument, or a throwaway \"config\" object with 6+ fields that exists solely to wrap what would otherwise be positional args (genuine reusable domain types like `HttpClientConfig` are fine).\n\n**When detected:** Group related parameters into a typed value object with a domain name. If 4+ independent inputs are genuinely required, the justification must be SPECIFIC. See [`references/code-smells.md` Smell 2](references/code-smells.md#smell-2--function-with-more-than-3-parameters) for examples in every language.\n\n### Smell 3 — Redundant verification after a destructive action\n\nPerforming a delete/remove/clear/drop and then immediately querying to \"confirm\" the thing is gone. **The operation's contract IS the verification.** Re-checking is AI-generated defensive bloat that wastes cycles and teaches the reader the operation is unreliable — which it is not. Same smell: calling a setter then getting to \"confirm\", writing a file then reading it back, inserting a row then SELECT-ing it, pushing to an array then checking `.length`.\n\n**When detected:** Delete the verification code. Trust the operation's contract. If the operation can genuinely fail silently, fix the operation — do not paper over it with a post-check. See [`references/code-smells.md` Smell 3](references/code-smells.md#smell-3--redundant-verification-after-a-destructive-action) for examples.\n\n### Smell 4 — Negative-form names and conditions\n\nNaming variables, functions, or flags by the **absence** of a quality (`isNotValid`, `noErrors`, `cannotProceed`, `DisableLogging`) instead of its **presence** (`isValid`, `isClean`, `canProceed`, `LoggingEnabled`). Every negation forces the reader to invert mentally; two negations (`if !isNotReady`) become a logic puzzle nobody reviews confidently.\n\n**When detected:** Rename to the positive form and invert the branch logic. Negation IS appropriate in guard clauses (`if !authorized { return }`) and filters (`items.filter(|x| !x.is_expired())`) — the negative form is the intent there. See [`references/code-smells.md` Smell 4](references/code-smells.md#smell-4--negative-form-names-and-conditions) for the full naming table and examples.\n\n---\n\n## LOGGING — CROSS-CUTTING RULES\n\nLogging is part of the code you ship, and it has iron rules of its own: levels chosen by naming the consumer (never by severity vibes), placement at decision points (never inside helpers), stable messages with structured fields — and, above everything else, **the project's existing practice wins: a project with a designated logger gets that logger and nothing else, and a project that does not log does not get logging uninvited.**\n\n**Read [`references/logging.md`](references/logging.md) BEFORE the change** whenever your edit adds or modifies log lines, sets up a logger or a new service entrypoint, or handles errors at a boundary.\n\n---\n\n## MANDATORY POST-WRITE REVIEW LOOP\n\n**This runs EVERY time you finish writing or substantively editing code, before you claim the task is done.** No exceptions.\n\n### Step 1 — measure\n\nFor every file you created or modified:\n\n```bash\nawk '!/^[[:space:]]*$/ && !/^[[:space:]]*(\\/\\/|#|--)/' <file> | wc -l\n```\n\nOr run the per-language checker the skill ships:\n\n```bash\n# Python\nuv run scripts/python/check-no-excuse-rules.py <changed paths>\n# Rust\nbash scripts/rust/check-no-excuse-rules.sh <changed paths>\n# TypeScript\nbun run scripts/typescript/check-no-excuse-rules.ts <changed paths>\n```\n\n### Step 2 — interpret\n\n| Pure LOC | Verdict | Required action |\n|---|---|---|\n| ≤ 200 | Healthy | continue |\n| 200 - 250 | **Warning band** | State that fact and propose a split if the next edit will add lines. |\n| > 250 | **DEFECT** | Do NOT commit new lines to this file. Refactor now: split the touched unit before adding lines, except for rare SIZE_OK or pure-data-table exceptions. |\n\n### Step 3 — architectural self-review (always, even at 80 LOC)\n\nAfter every code-writing session, answer these out loud (in your reply) before declaring done:\n\n1. **Single responsibility?** Can I name what this file owns in one short noun phrase? If the answer needs the word \"and\", split.\n2. **Boundary purity?** Did I parse untrusted input into a typed value at the boundary, or did I pass `dict[str, Any]` / `serde_json::Value` / `unknown` past the boundary? If the latter, fix it.\n3. **Variant discrimination?** Did I use `if`/`elif`/`else` (or `switch` without `assertNever`, or `match` without `assert_never`) anywhere to discriminate on a tagged type or enum? If yes, rewrite as exhaustive match.\n4. **Escape hatches?** Any `Any`, `# type: ignore`, `unwrap`, `expect` outside `main`/tests, `as` numeric cast, `!`, `@ts-ignore`, `@ts-expect-error`, `#[allow]` on a real warning? If yes, fix the type or document why with a comment.\n5. **Defensive layer?** Any null check, try/except, or `isinstance` guarding a value the type system already proves? If yes, delete.\n6. **Helpers for one-off?** Any function, class, or trait introduced for a single caller that will never get a second caller? If yes, inline — axiom 0 should have caught it pre-write; this is the backstop.\n7. **Tests?** Is the behavior I just introduced locked by a test that would fail if I revert this commit?\n8. **Parameter bloat?** Any function I wrote or modified that takes more than 3 parameters — or smuggles them through a dict/kwargs/`...args`/throwaway options object? If yes, group related params into a typed value object. See [Smell 2](references/code-smells.md#smell-2--function-with-more-than-3-parameters).\n9. **Redundant verification?** Did I perform a destructive action (delete, remove, clear) and then immediately re-query to \"confirm\" it worked? Did I call a setter then a getter to \"verify\"? If yes, delete the verification — the operation's contract IS the proof. See [Smell 3](references/code-smells.md#smell-3--redundant-verification-after-a-destructive-action).\n10. **Negative naming?** Any variable, function, or flag named by the absence of a quality (`isNotValid`, `noErrors`, `DisableX`) when a positive name (`isValid`, `isClean`, `EnableX`) would work? If yes, rename to positive form and invert the branch. See [Smell 4](references/code-smells.md#smell-4--negative-form-names-and-conditions).\n11. **Logging?** If I touched log lines, logger setup, or error boundaries: did I follow the project's existing practice (including its absence)? Is every new line leveled by its consumer, placed at a decision point, and message-stable with data in fields? See [`references/logging.md`](references/logging.md).\n\n**If any answer fails, fix it before declaring done.** This loop is the difference between \"the code compiles\" and \"the code is correct.\"\n\n### Step 4 — if you need to refactor right now, invoke the right skill\n\n- Any code smell from the [CODE SMELLS section](#code-smells--automatic-review-triggers) fired (250+ LOC, >3 params, redundant verification, negative naming), or step 3 surfaced more than two issues: **load the `refactor` skill** and execute its safe-refactor protocol (codemap, plan, LSP-driven edits, test after each step). Do not improvise a refactor under time pressure — the refactor skill exists precisely so you do not corrupt behavior while reshaping structure.\n- You inherited a branch with AI-generated patterns (broad `except`, redundant null checks, vague TODOs, oversized modules, dead helpers, redundant post-action verification): **load the `remove-ai-slops` skill** to do a categorized branch-scope cleanup with regression tests pinned first.\n\nThese two skills are not optional cosmetics. They are the recovery path for the smells this loop is designed to catch.\n\n---\n\n## Companion skills - explicit invocation triggers\n\n| Trigger | Skill to load | Why |\n|---|---|---|\n| Any [code smell](#code-smells--automatic-review-triggers) fires (250+ LOC, >3 params, redundant verification), OR the post-write loop surfaces 2+ issues, OR the user says \"reshape this\", \"extract this\", \"clean this up\" | `refactor` | Safe codemap-driven multi-step refactor with LSP + tests after each step. Never improvise a structural change. |\n| Recent branch contains AI-authored patterns (broad except, dead helpers, vague comments, oversized files, redundant post-action verification), OR the user says \"remove slop\", \"clean AI code\", \"deslop\" | `remove-ai-slops` | Tests pinned FIRST, then categorized parallel cleanup, then quality gates. Behavior-preserving. |\n| Rust code touches `unsafe`, `*mut`, `*const`, `MaybeUninit`, FFI, `unsafe impl Send/Sync`, or a custom lock-free primitive | `references/rust-ub/` | Full UB taxonomy + Miri strictness escalation. Every `unsafe` block must survive Miri Level 3 (strict provenance + symbolic alignment + preemption) before it ships. |\n\n---\n\n## Per-language jump table\n\n**Stop. Read the matching reference fully before writing code.**\n\n### Python (`.py`, `.pyi`)\n\n**READ `references/python/README.md` FIRST.** Then load on demand:\n\n| Need | Load |\n|---|---|\n| Strict pyproject.toml / basedpyright / ruff config | `references/python/pyproject-strict.md` |\n| Type patterns (`NewType`, `Final`, `TypeGuard`, `Protocol`) | `references/python/type-patterns.md` |\n| Data modeling (Pydantic vs dataclass vs TypedDict vs StrEnum) | `references/python/data-modeling.md` |\n| Error handling (typed exceptions, exhaustive match, union returns) | `references/python/error-handling.md` |\n| Async with anyio (task groups, cancel scopes, channels) | `references/python/async-anyio.md` |\n| httpx2 production defaults (HTTP/2, brotli+zstd, pool tuning) | `references/python/httpx2-optimization.md` |\n| **orjson** in hot paths (FastAPI integration, Pydantic v2 `model_dump_json` vs orjson, Redis/queue/log) | `references/python/orjson-stack.md` |\n| Data processing with polars + duckdb (NEVER pandas) | `references/python/data-processing.md` |\n| FastAPI + SQLAlchemy 2.x async stack | `references/python/fastapi-stack.md` |\n| pydantic-ai agents | `references/python/pydantic-ai.md` |\n| Textual TUI | `references/python/textual-tui.md` |\n| Disposable PEP 723 scripts | `references/python/one-liners.md` |\n| Canonical library defaults | `references/python/libraries.md` |\n\n### Rust (`.rs`, `Cargo.toml`)\n\n**READ `references/rust/README.md` FIRST.** It defines the five pillars (explicit allocation, compile-time proof, zero hidden cost, type-encoded invariants, deterministic cleanup) and the post-write review checklist. Then load on demand:\n\n| Need | Load |\n|---|---|\n| **Arena allocation, const fn, zero-alloc APIs, bitfield, scopeguard, errdefer, Zig-like patterns** | **`references/rust/zero-cost-safety.md`** |\n| Strict `Cargo.toml` lints + profile + workspace config | `references/rust/cargo-strict.md` |\n| Type-state and newtype patterns (Chris Allen's `Point<Screen>` rule) | `references/rust/type-state.md` |\n| `unsafe` discipline (safe wrapper + SAFETY comment + miri proof) | `references/rust/unsafe-discipline.md` |\n| Async with tokio (JoinSet, cancellation, select, blocking work) | `references/rust/async-tokio.md` |\n| Concurrency primitives (locks, atomics, channels, loom) | `references/rust/concurrency.md` |\n| axum + sqlx + tracing + tower HTTP stack | `references/rust/axum-stack.md` |\n| clap + color-eyre + tracing + indicatif CLI stack | `references/rust/clap-stack.md` |\n| Property tests (proptest) + snapshot tests (insta) | `references/rust/proptest-insta.md` |\n| Disposable `rust-script` scripts | `references/rust/one-liners.md` |\n| Canonical library defaults | `references/rust/libraries.md` |\n| **ANY `unsafe` / FFI / `MaybeUninit` / lock-free work** | **`references/rust-ub/` (full directory)** |\n\n### TypeScript (`.ts`, `.tsx`, `.mts`, `.cts`)\n\n**READ `references/typescript/README.md` FIRST.** Then load on demand:\n\n| Need | Load |\n|---|---|\n| Strict tsconfig + Biome config | `references/typescript/tsconfig-strict.md` |\n| Type patterns (branded types, `as const`, `satisfies`, narrowing, `assertNever`) | `references/typescript/type-patterns.md` |\n| Data modeling (type vs interface vs Zod, readonly, parse-don't-validate) | `references/typescript/data-modeling.md` |\n| Error handling (Result, typed errors, union vs throw, AbortSignal timeouts) | `references/typescript/error-handling.md` |\n| Bootstrapping a new project (Bun, pnpm, Hono, Vite) | `references/typescript/bootstrap.md` |\n| Hono backend stack (hono-openapi, Scalar, Swagger, Zod v4) | `references/typescript/backend-hono.md` |\n\n### Go (`.go`, `go.mod`, `go.sum`, `.golangci.yml`, `*.proto`)\n\n**READ `references/go/README.md` FIRST.** Then load on demand:\n\n| Need | Load |\n|---|---|\n| Library defaults (gin vs chi, sqlc, slog, the 2026 stack reasoning) | `references/go/libraries.md` |\n| Canonical strict `.golangci.yml` (v2) with per-linter rationale | `references/go/golangci-strict.md` |\n| Project layout, Taskfile, CI, `go.mod` template | `references/go/bootstrap.md` |\n| Type patterns (named types, smart constructors, sealed interfaces, generics) | `references/go/type-patterns.md` |\n| Data modeling — the three layers of validation (validator/v10 → smart ctor → sqlc) | `references/go/data-modeling.md` |\n| Error handling (`errors.Is/As`, typed errors, `%w` wrapping, no panic) | `references/go/error-handling.md` |\n| Concurrency (`context.Context`, `errgroup`, channels, locks, `-race`, `goleak`) | `references/go/concurrency.md` |\n| HTTP backend stack (gin + slog + validator + pgx, middleware ordering, SSE, WS) | `references/go/backend-stack.md` |\n| RPC stack (Connect-Go default, grpc-go fallback, protovalidate, Buf) | `references/go/grpc-connect.md` |\n| CLI stack (cobra + slog + huh) | `references/go/cobra-stack.md` |\n| Database stack (sqlc + pgx + goose + testcontainers) | `references/go/sqlc-pgx.md` |\n| TUI stack (bubbletea v2 + bubbles v2 + lipgloss v2; **CJK / IME support**) | `references/go/bubbletea-v2.md` |\n| Testing (Given/When/Then, table-driven, fakes-over-mocks, autogold, rapid) | `references/go/testing.md` |\n| Disposable `go run` scripts | `references/go/one-liners.md` |\n\n---\n\n## Activation\n\nThis skill activates whenever you are writing or modifying any `.py`, `.pyi`, `.rs`, `.ts`, `.tsx`, `.mts`, `.cts`, `.go` file, or any project manifest (`pyproject.toml`, `Cargo.toml`, `package.json`, `tsconfig.json`, `biome.json`, `go.mod`, `go.sum`, `.golangci.yml`, `Taskfile.yml`, `buf.yaml`, `sqlc.yaml`). **Even one-off scripts get the full treatment** - that is the whole point of `uv run` + PEP 723, `rust-script`, `bun run`, and `go run` + `//go:build ignore`: production hygiene with throwaway ergonomics.\n\nThe references contain the recipes. **Read them before writing code. Re-read them when the model drifts.** The post-write review loop is non-negotiable.\n","exit_code":0,"duration":{"secs":0,"nanos":84954890},"formatted_output":"---\nname: programming\ndescription: \"MUST USE for ANY work on .py .pyi .rs .ts .tsx .mts .cts .go files. One philosophy: strict types, modern stacks (Pydantic v2 / serde+thiserror / Zod / gin+sqlc+pgx+slog), modern toolchains (uv+basedpyright+ruff / cargo+clippy+miri / Bun+Biome+tsc / gofumpt+golangci-lint v2+nilaway+go-race), parse-don't-validate, exhaustive match, typed errors, no any/unwrap/panic, 250 LOC ceiling, TDD, consumer-routed logging. Routes to references/{python,rust,typescript,rust-ub,go}/ + references/logging.md. Triggers: write/edit Python/Rust/TypeScript/Go code, new project, gin server, bubbletea TUI, CJK IME, connect-go RPC, sqlc pgx, branded ids, exhaustive match, unsafe Rust, miri, oversized file, refactor, TDD, e2e test, logging, log levels, structured logging, observability, arena, allocator, bumpalo, const fn, const generics, comptime, zero-alloc, bitfield, repr, scopeguard, errdefer, Zig-like, zerocopy, packed struct.\"\n---\n\n# Programming\n\nYou are a lazy senior engineer — lazy meaning efficient, never careless. **The best code is the code never written; the code you do write is type-strict, stack-first, async-correct, and architecturally honest about size.**\n\nThis skill is an index. The hard per-language rules live under `references/`. Load the language-specific reference **before** writing a single line of code.\n\n---\n\n## PHASE 0 — LANGUAGE GATE (RUN THIS FIRST, EVERY TIME)\n\n**DO NOT WRITE OR EDIT A SINGLE LINE OF CODE BEFORE COMPLETING THIS GATE.**\n\n1. **Identify the language** from the file extension or the user's request.\n2. **STOP** and read the matching reference set:\n\n | File / Language | MANDATORY reading (load `Read` tool on every file below) |\n |---|---|\n | `.py`, `.pyi`, \"Python\" | `references/python/README.md` + every file under `references/python/` that the README tells you to load on demand |\n | `.rs`, `Cargo.toml`, \"Rust\" | `references/rust/README.md` + every file under `references/rust/` that the README tells you to load on demand. **IF the change touches `unsafe`, `*mut`, `*const`, `MaybeUninit`, FFI, `unsafe impl Send/Sync`, or a custom lock-free primitive: ALSO load `references/rust-ub/README.md` plus every file under `references/rust-ub/`.** |\n | `.ts`, `.tsx`, `.mts`, `.cts`, \"TypeScript\" | `references/typescript/README.md` + every file under `references/typescript/` that the README tells you to load on demand |\n | `.go`, `go.mod`, `go.sum`, `.golangci.yml`, `*.proto` next to a Go module, \"Go\" / \"Golang\" | `references/go/README.md` + every file under `references/go/` that the README tells you to load on demand |\n\n3. Only after the references are loaded, apply the **shared philosophy** below plus the per-language iron list from the reference.\n\n**No exceptions for \"small\" or \"one-off\" code.** The whole point of the modern toolchain (uv + PEP 723, `rust-script`, Bun) is that disposable scripts cost nothing to write with full discipline.\n\n---\n\n## Shared philosophy (all three languages)\n\nThese are not style preferences. They are the seven axioms every recipe in `references/` derives from.\n\n0. **The best code is the code never written.** Before writing, stop at the first rung that holds: (1) does this need to exist at all? (YAGNI) (2) does this codebase already have it? — reuse the helper or pattern, do not re-implement. (3) does the standard library do it? (4) does a native platform feature cover it? (5) does an installed dependency solve it? (6) can it be one line? (7) only then, write the minimum that works. Climb the ladder *after* you understand the problem and trace the real flow end to end — the smallest diff in the wrong place is a second bug, not laziness. The ladder is a fast decision, not a written essay: pick the rung and move. **Bug fix = root cause, not symptom.** A ticket names a symptom; grep every caller of the function you touch and fix the shared seam once — one guard at the source is a smaller, more correct diff than one guard per caller, and patching only the path the ticket names leaves a sibling caller broken.\n\n1. **The type system is your proof system.** Make illegal states unrepresentable. The compiler / type checker is the cheapest test you will ever run. If a bug can be expressed as a type error, it is *required* to be expressed as a type error.\n\n2. **Parse, don't validate.** Untrusted input crosses a boundary exactly once - at the boundary it is parsed into a typed value (Pydantic v2 in Python, `serde` + `#[derive]` in Rust, Zod in TypeScript). Inside the boundary, code receives typed values and never re-validates. The boundary owns trust; the interior owns logic.\n\n3. **One name = one concept.** A `UserId` is not a `string`. A `Seconds` is not a `Milliseconds`. Use `NewType` (Python), newtype tuple structs (Rust), or branded types (TypeScript) for every distinct semantic primitive. The compiler refuses to let two semantic units mix.\n\n4. **Exhaustive variant matching, always.** Discriminated unions and enums are matched exhaustively. Python: `match` + `case unreachable: assert_never(unreachable)`. Rust: `match` (the compiler enforces). TypeScript: `switch` + `assertNever`. **`if`/`elif`/`else` is forbidden for discriminating on a tagged variant** - it silently swallows new variants.\n\n5. **Trust framework guarantees. Validate only at boundaries.** No null checks for values the type system already proves non-null. No `try/except` around code that cannot raise. No `unwrap`/`!`/`as` to paper over a contract you should have encoded in types. No defensive layer for a scenario you cannot name.\n\n6. **Test-driven, with the right shape of test.** No production line ships without a failing test that proves it was needed. Behavior is locked by tests, not by hope. See the TDD discipline below.\n\n---\n\n## TDD DISCIPLINE — NON-NEGOTIABLE\n\n**Every change follows the red → green → refactor loop.** The order is mandatory; reverse it and you have written speculative code.\n\n### The order\n\n1. **Red.** Write a failing test that names the behavior in `Given / When / Then`. Run it. *Confirm it fails for the right reason* — not a typo, not an import error. A test that fails because the function does not exist yet is the right reason. A test that fails because of a missing import is not.\n2. **Green.** Write the minimum code to make the test pass. Resist adding the second case until the first passes. The second case is the next red.\n3. **Refactor.** With the test green, restructure ruthlessly. The test is your safety net. If the test is hard to refactor against, the test is bad — fix the test before the code.\n\n### The shape of the test pyramid\n\nEvery feature ships with all three rungs, sized in this proportion:\n\n| Rung | Count | Purpose | Speed budget |\n|---|---|---|---|\n| **Unit** | many | Pure-function correctness for every meaningful input class (happy + edges + boundaries + error paths) | < 10 ms each |\n| **Integration** | some | The real adapter against the real downstream (DB, queue, HTTP) — via `testcontainers`, `httptest`, or equivalent. NEVER a unit test pretending to be integration. | < 1 s each |\n| **E2E scenario** | few | One narrative per user-visible outcome. Spins the binary or the full app; drives it through its real surface (HTTP route, CLI invocation, TUI keystroke). Asserts the *observable outcome*, not internal state. | seconds, run on CI |\n\nIf a feature has zero E2E coverage, it is undone — even if every unit test passes.\n\n### Given / When / Then is mandatory\n\nEvery test — unit, integration, E2E — is structured by these three blocks. Names follow `Test_<Behavior>_when_<Condition>` or the language idiom (`it(\"<does X> when <Y>\")`, `#[test] fn behavior_when_condition`).\n\n```\nGiven: the preconditions and fixtures\nWhen: the single action under test\nThen: the observable outcome AND only that outcome\n```\n\nOne `When` per test. Multiple `When`s = multiple tests. The `Then` asserts only what changed because of the `When` — not unrelated invariants.\n\n### Less mock, the better\n\nMocks are a last resort, not a default. The priority order:\n\n1. **Real object.** Use it when constructable in <1 ms (most domain types, pure functions, value objects).\n2. **In-memory fake.** A real implementation of the interface backed by a map/slice — for stores, caches, queues. The fake has its OWN test that proves it behaves like the real one.\n3. **Testcontainer / sandbox.** Real Postgres, real Redis, real S3-compatible (MinIO), via `testcontainers`. Slow but truthful.\n4. **HTTP-level fake.** `httptest.Server` (Go), `respx` (Python), `msw` (TS) — fake at the wire, not at the SDK.\n5. **Mock.** Only when 1–4 are genuinely infeasible (clock, randomness, external SaaS with no sandbox). Then mock the **narrowest** seam — never an entire service. A mock that returns whatever the test wants is a tautology and proves nothing.\n\n**The rule**: if your test fails when the production code's *implementation* changes but its *behavior* did not, the test is over-mocked. Delete the mock; assert on observable outputs.\n\n### Efficient AND accurate — both, not either\n\n- **Accurate**: the test fails for the bug it names, and only that bug. No incidental coupling to format, ordering, whitespace, or unrelated fields. Assert on the *contract*, not on the dump.\n- **Efficient**: the whole unit suite runs in < 30 seconds on a developer laptop. The whole integration suite in < 5 minutes. If you cross those budgets, profile and split — fast tests run on every save, slow ones run on push.\n- **Deterministic**: no `sleep`, no wall-clock dependence, no order dependence (`-shuffle=on`, pytest-randomly, vitest random seed). Inject a `Clock`. Subscribe to the event, do not poll for it. Time-based flake is a bug, not a test issue.\n- **Isolated**: every test starts from a known fixture and tears down. `t.TempDir()`, `t.Setenv()`, transactional rollback for DB tests. Two tests passing individually but failing together is a fixture leak — fix it immediately.\n\n### Prompt tests follow the same rule\n\nWhen tests cover LLM prompts or agent outputs, assert on **parsed structure, decisions, or rule data**, never on exact prompt strings. Pinning a sentence is brittle pretend-coverage; asserting that the prompt instructs the model to refuse on category X is real coverage.\n\n### Anti-patterns the skill rejects\n\n| Anti-pattern | Why it fails | Fix |\n|---|---|---|\n| Writing code first, tests \"to add later\" | Tests-after rationalize the existing design, even when wrong. | Red first. Always. |\n| One mega-test asserting 12 things | First failure hides the next 11. | Split by `Then` clause — one assertion class per test. |\n| Mocking every collaborator | Test passes regardless of real behavior. | Use a fake or the real thing. Mock only true unmockables. |\n| `time.sleep(0.1)` to \"let it finish\" | Flake guaranteed. | Subscribe to the completion signal; bounded await. |\n| Snapshot tests for everything | Locks formatting, not behavior. | Snapshots for *structure* (CLI help, JSON shape). Assertions for *behavior*. |\n| Removing a failing test to \"unblock CI\" | You just deleted a bug report. | Fix the code or fix the test — never delete to silence. |\n| `assert result is not None` and stopping there | Passes when result is garbage. | Assert the *value*, not its existence. |\n| Single happy-path E2E, no edges | Most bugs live on edges. | Edges are unit-test territory — but include at least one E2E that exercises an error path. |\n\n---\n\n## Cross-language iron list\n\nApply unless the per-language reference overrides with something stricter.\n\n| Rule | Python | Rust | TypeScript | Go |\n|---|---|---|---|---|\n| Immutable by default | `@dataclass(frozen=True, slots=True)` / Pydantic `frozen=True` | every binding is `let` (not `let mut`) unless mutation is the documented purpose | every field is `readonly`; arrays are `readonly T[]` | value types, unexported fields, no mutation methods unless mutation is the purpose |\n| Branded primitives | `UserId = NewType(\"UserId\", int)` | `struct UserId(u64);` (newtype tuple) | `type UserId = Brand<string, \"UserId\">` | `type UserID string` + smart constructor with unexported field |\n| Exhaustive variant matching | `match` + `assert_never` | `match` (compiler-enforced) | `switch` + `assertNever` | sealed interface + type switch + **`exhaustive` linter** (the compiler will not help) |\n| No untyped escape hatches | no `Any` in public sigs, no `cast`, no `# type: ignore` | no `unwrap`/`expect` outside `main`/tests, no `as` for narrowing, no `#[allow]` to silence real warnings | no `any`, no `as` (except `as const`, `satisfies`), no `!`, no `@ts-ignore`, no `@ts-expect-error` | no `interface{}` / bare `any` in domain sigs; no `_ = err`; no `//nolint` without reason |\n| No bare error strings | typed exception dataclass with `__str__` | `thiserror` enum (lib) or `anyhow` with `.context(...)` (app) | `Error` subclass with typed fields | sentinel `errors.New` + typed `*XError` struct; wrap with `%w`; check via `errors.Is/As` |\n| Boundary catch only | catch the exact exception you expect; broad `except Exception` only in `main()`, with logging + re-raise | `?` everywhere; never `panic!` in library code | `catch` must narrow with `instanceof` and re-throw or convert; no empty catch | every `(T, error)` checked; `panic` only in `main`/tests; one `httperr.Write` funnel in handlers |\n| Resources via RAII | `with` (sync) / `async with` (async) | `Drop` impl or RAII guard | `using`/`await using` (TC39 explicit resource management) | `defer x.Close()` immediately after acquisition; `bodyclose`/`sqlclosecheck` linters enforce |\n| Async runtime is mandatory | `anyio` (NEVER bare `asyncio`) | `tokio` (`async-std` is unmaintained) | platform-native async (Bun/Node) with structured cancellation via `AbortSignal` | `context.Context` as first param + `errgroup` for structured concurrency; `-race` on every test |\n| Modern HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) with HTTP/2 + brotli + zstd | `reqwest` with rustls | `ky` (default) / `undici` direct API (Node perf) - NEVER bare `fetch` in prod | stdlib `net/http.Client` with tuned `Transport` + `go-retryablehttp` for retry/backoff |\n| No parameter mutation | params are inputs; produce a new value | `&mut` only when mutation is the documented purpose | parameters never reassigned (`noParameterAssign`) | value receivers when not mutating; pointer receivers only for genuine mutation; `copylocks` vet enforces |\n| No helpers for one-off | inline a 3-line operation; do not abstract until the second caller | same | same | same |\n\n---\n\n## Modern ecosystem - canonical libraries (2026)\n\nUse these unless the project's manifest explicitly picks something else.\n\n| Domain | Python | Rust | TypeScript | Go |\n|---|---|---|---|---|\n| Data validation / boundary parse | **Pydantic v2** | **serde** + `#[derive(Deserialize)]` + `validator` | **Zod v4** (Standard Schema) | `validator/v10` (HTTP) + `protovalidate` (proto) + smart constructors (domain) |\n| Internal value object | `@dataclass(frozen=True, slots=True)` | newtype tuple struct or plain `struct` | `type` alias with `readonly` | struct with unexported fields + `NewX(...)` constructor |\n| Error types | typed exception dataclass | `thiserror` (lib) + `anyhow` (app) | `Error` subclass + Result pattern | sentinel `errors.New` + typed `*XError` struct + `%w` wrap |\n| HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) | `reqwest` | `ky` / `undici` | stdlib `net/http` + `go-retryablehttp` |\n| Web framework | **FastAPI** | **axum** | **Hono** + `hono-openapi` | **gin** (de facto, ~48%) / `chi` (minimalist) / `connect-go` (RPC) |\n| ORM / DB | SQLAlchemy 2.x async + `asyncpg` | `sqlx` (compile-time checked) | **Drizzle** | **sqlc** (codegen from `.sql`) + `pgx/v5` + `goose` migrations |\n| CLI | **typer** + `rich` | **clap** (derive) + `color-eyre` + `indicatif` | `@clack/prompts` + `commander` | **cobra** + `huh` (prompts) + `slog` |\n| Logging / observability | `structlog` (prod) or `rich.logging` (dev) | **tracing** + `tracing-subscriber` | `pino` (structured JSON) | stdlib **`log/slog`** (NEVER logrus/zap/zerolog for new code) |\n| Testing | `pytest` | `cargo nextest` + `proptest` + `insta` | `bun test` / `vitest` | stdlib `testing` + `testify/require` + `goleak` + `autogold` + `rapid` + `testcontainers` |\n| Data / analytics | **polars** + **duckdb** + `numpy` (NEVER pandas) | `polars-rs` or `arrow` | (defer to backend service) | `arrow-go` + DuckDB-Go bindings + `gonum` |\n| LLM / agent | **pydantic-ai** | (call out to Python via subprocess) | **Vercel AI SDK** | direct `net/http` + Connect (langchaingo not recommended) |\n| TUI | **textual** | `ratatui` | `@clack/prompts` or ink | **bubbletea v2 RC** + `bubbles/v2` + `lipgloss/v2` (v2 mandatory for CJK IME) |\n| Config from env | **pydantic-settings** | `figment` or `config` | `zod` + `process.env` | `caarlos0/env/v11` (struct-tag env) |\n\nA bare default constructor for any of these (no timeouts, no pool tuning, no schema) is a bug. See the per-language reference for the canonical production defaults.\n\n---\n\n## Modern toolchain - the only acceptable setup\n\n| Tool category | Python | Rust | TypeScript | Go |\n|---|---|---|---|---|\n| Package / project manager | **uv** (NEVER pip/poetry/conda) | **cargo** + `cargo-nextest` + `cargo-machete` + `cargo-deny` | **Bun** (runtime + package manager); pnpm if Node is forced | **`go modules`** + `go work` for monorepos |\n| Type checker | **basedpyright** with `typeCheckingMode = \"all\"` | the Rust compiler with `-D warnings` + clippy `pedantic` + `nursery` + `cargo` groups | `tsc --noEmit` (or `tsgo` when available) with `strict` + `noUncheckedIndexedAccess` + `exactOptionalPropertyTypes` + `verbatimModuleSyntax` | the Go compiler + **`golangci-lint v2`** with the strict bundle + **`nilaway`** (nil-deref static analysis) |\n| Linter + formatter | **ruff** with `select = [\"ALL\"]` | `clippy` + `rustfmt` | **Biome** (single binary - replaces ESLint + Prettier) | **`gofumpt`** (stricter gofmt) + `goimports -local` + `golangci-lint v2` |\n| Test runner | **pytest** | **cargo-nextest** | `bun test` / `vitest` | stdlib `go test -race -shuffle=on -count=1` + `goleak` |\n| UB / soundness gate | (n/a) | **nightly miri** with strict provenance + Tree Borrows pass | (n/a) | **`nilaway`** + `-race` detector + `goleak` are the equivalent gate |\n| Disposable scripts | **PEP 723** inline metadata + `uv run script.py` | **rust-script** with inline `Cargo.toml` block | `bun run script.ts` | `//go:build ignore` + `go run script.go` |\n| Bootstrap a new project | `scripts/python/new-project.py` | `scripts/rust/new-project.py` | `scripts/typescript/new-project.ts` | `scripts/go/new-project.py` |\n| Pre-commit / CI gate | `ruff check . && basedpyright && pytest` | `cargo +nightly clippy -- -D warnings && cargo nextest run && cargo +nightly miri test` | `bunx biome check . && bunx tsc --noEmit && bun test` | `gofumpt -l . && golangci-lint run ./... && nilaway ./... && go test -race -shuffle=on -count=1 ./...` |\n\nA `tsconfig.json` with `\"strict\": true` alone is **not** strict. The reference enumerates the additional flags. Same for `pyproject.toml` and `Cargo.toml` - the references contain the canonical full configuration.\n\n---\n\n## CODE SMELLS — AUTOMATIC REVIEW TRIGGERS\n\nMost smells below are design review triggers: STOP, re-examine the code, and either fix the smell or justify carrying it with a SPECIFIC reason. **The 250 pure LOC ceiling is stricter: >250 is a DEFECT. Refactor before adding lines except for rare SIZE_OK or pure-data-table exceptions.**\n\nFull rationale, measurement methods, workaround detection, and split examples: **[`references/code-smells.md`](references/code-smells.md)**.\n\n### Smell 1 — File exceeds 250 pure LOC\n\nA source file past 250 non-blank, non-comment lines has outgrown a single reviewer's working memory. The module is almost certainly doing more than one thing. Measure: `awk '!/^[[:space:]]*$/ && !/^[[:space:]]*(\\/\\/|#|--)/' <file> | wc -l`.\n\n**When detected:** Name what the file owns in one short noun phrase. If the answer needs \"and\", the file needs splitting. Load `/refactor` and split by responsibility. If the file genuinely cannot be split (generated parser, indivisible state machine), mark with `// allow: SIZE_OK — <reason>`.\n\n### Smell 2 — Function with more than 3 parameters\n\nMore than 3 arguments signals the function is doing too much, or that related parameters belong in a typed struct. **Workarounds count as the same smell** — passing `dict`/`Record<string, unknown>`/`map[string]any`/`**kwargs`/`...args` to smuggle parameters through one argument, or a throwaway \"config\" object with 6+ fields that exists solely to wrap what would otherwise be positional args (genuine reusable domain types like `HttpClientConfig` are fine).\n\n**When detected:** Group related parameters into a typed value object with a domain name. If 4+ independent inputs are genuinely required, the justification must be SPECIFIC. See [`references/code-smells.md` Smell 2](references/code-smells.md#smell-2--function-with-more-than-3-parameters) for examples in every language.\n\n### Smell 3 — Redundant verification after a destructive action\n\nPerforming a delete/remove/clear/drop and then immediately querying to \"confirm\" the thing is gone. **The operation's contract IS the verification.** Re-checking is AI-generated defensive bloat that wastes cycles and teaches the reader the operation is unreliable — which it is not. Same smell: calling a setter then getting to \"confirm\", writing a file then reading it back, inserting a row then SELECT-ing it, pushing to an array then checking `.length`.\n\n**When detected:** Delete the verification code. Trust the operation's contract. If the operation can genuinely fail silently, fix the operation — do not paper over it with a post-check. See [`references/code-smells.md` Smell 3](references/code-smells.md#smell-3--redundant-verification-after-a-destructive-action) for examples.\n\n### Smell 4 — Negative-form names and conditions\n\nNaming variables, functions, or flags by the **absence** of a quality (`isNotValid`, `noErrors`, `cannotProceed`, `DisableLogging`) instead of its **presence** (`isValid`, `isClean`, `canProceed`, `LoggingEnabled`). Every negation forces the reader to invert mentally; two negations (`if !isNotReady`) become a logic puzzle nobody reviews confidently.\n\n**When detected:** Rename to the positive form and invert the branch logic. Negation IS appropriate in guard clauses (`if !authorized { return }`) and filters (`items.filter(|x| !x.is_expired())`) — the negative form is the intent there. See [`references/code-smells.md` Smell 4](references/code-smells.md#smell-4--negative-form-names-and-conditions) for the full naming table and examples.\n\n---\n\n## LOGGING — CROSS-CUTTING RULES\n\nLogging is part of the code you ship, and it has iron rules of its own: levels chosen by naming the consumer (never by severity vibes), placement at decision points (never inside helpers), stable messages with structured fields — and, above everything else, **the project's existing practice wins: a project with a designated logger gets that logger and nothing else, and a project that does not log does not get logging uninvited.**\n\n**Read [`references/logging.md`](references/logging.md) BEFORE the change** whenever your edit adds or modifies log lines, sets up a logger or a new service entrypoint, or handles errors at a boundary.\n\n---\n\n## MANDATORY POST-WRITE REVIEW LOOP\n\n**This runs EVERY time you finish writing or substantively editing code, before you claim the task is done.** No exceptions.\n\n### Step 1 — measure\n\nFor every file you created or modified:\n\n```bash\nawk '!/^[[:space:]]*$/ && !/^[[:space:]]*(\\/\\/|#|--)/' <file> | wc -l\n```\n\nOr run the per-language checker the skill ships:\n\n```bash\n# Python\nuv run scripts/python/check-no-excuse-rules.py <changed paths>\n# Rust\nbash scripts/rust/check-no-excuse-rules.sh <changed paths>\n# TypeScript\nbun run scripts/typescript/check-no-excuse-rules.ts <changed paths>\n```\n\n### Step 2 — interpret\n\n| Pure LOC | Verdict | Required action |\n|---|---|---|\n| ≤ 200 | Healthy | continue |\n| 200 - 250 | **Warning band** | State that fact and propose a split if the next edit will add lines. |\n| > 250 | **DEFECT** | Do NOT commit new lines to this file. Refactor now: split the touched unit before adding lines, except for rare SIZE_OK or pure-data-table exceptions. |\n\n### Step 3 — architectural self-review (always, even at 80 LOC)\n\nAfter every code-writing session, answer these out loud (in your reply) before declaring done:\n\n1. **Single responsibility?** Can I name what this file owns in one short noun phrase? If the answer needs the word \"and\", split.\n2. **Boundary purity?** Did I parse untrusted input into a typed value at the boundary, or did I pass `dict[str, Any]` / `serde_json::Value` / `unknown` past the boundary? If the latter, fix it.\n3. **Variant discrimination?** Did I use `if`/`elif`/`else` (or `switch` without `assertNever`, or `match` without `assert_never`) anywhere to discriminate on a tagged type or enum? If yes, rewrite as exhaustive match.\n4. **Escape hatches?** Any `Any`, `# type: ignore`, `unwrap`, `expect` outside `main`/tests, `as` numeric cast, `!`, `@ts-ignore`, `@ts-expect-error`, `#[allow]` on a real warning? If yes, fix the type or document why with a comment.\n5. **Defensive layer?** Any null check, try/except, or `isinstance` guarding a value the type system already proves? If yes, delete.\n6. **Helpers for one-off?** Any function, class, or trait introduced for a single caller that will never get a second caller? If yes, inline — axiom 0 should have caught it pre-write; this is the backstop.\n7. **Tests?** Is the behavior I just introduced locked by a test that would fail if I revert this commit?\n8. **Parameter bloat?** Any function I wrote or modified that takes more than 3 parameters — or smuggles them through a dict/kwargs/`...args`/throwaway options object? If yes, group related params into a typed value object. See [Smell 2](references/code-smells.md#smell-2--function-with-more-than-3-parameters).\n9. **Redundant verification?** Did I perform a destructive action (delete, remove, clear) and then immediately re-query to \"confirm\" it worked? Did I call a setter then a getter to \"verify\"? If yes, delete the verification — the operation's contract IS the proof. See [Smell 3](references/code-smells.md#smell-3--redundant-verification-after-a-destructive-action).\n10. **Negative naming?** Any variable, function, or flag named by the absence of a quality (`isNotValid`, `noErrors`, `DisableX`) when a positive name (`isValid`, `isClean`, `EnableX`) would work? If yes, rename to positive form and invert the branch. See [Smell 4](references/code-smells.md#smell-4--negative-form-names-and-conditions).\n11. **Logging?** If I touched log lines, logger setup, or error boundaries: did I follow the project's existing practice (including its absence)? Is every new line leveled by its consumer, placed at a decision point, and message-stable with data in fields? See [`references/logging.md`](references/logging.md).\n\n**If any answer fails, fix it before declaring done.** This loop is the difference between \"the code compiles\" and \"the code is correct.\"\n\n### Step 4 — if you need to refactor right now, invoke the right skill\n\n- Any code smell from the [CODE SMELLS section](#code-smells--automatic-review-triggers) fired (250+ LOC, >3 params, redundant verification, negative naming), or step 3 surfaced more than two issues: **load the `refactor` skill** and execute its safe-refactor protocol (codemap, plan, LSP-driven edits, test after each step). Do not improvise a refactor under time pressure — the refactor skill exists precisely so you do not corrupt behavior while reshaping structure.\n- You inherited a branch with AI-generated patterns (broad `except`, redundant null checks, vague TODOs, oversized modules, dead helpers, redundant post-action verification): **load the `remove-ai-slops` skill** to do a categorized branch-scope cleanup with regression tests pinned first.\n\nThese two skills are not optional cosmetics. They are the recovery path for the smells this loop is designed to catch.\n\n---\n\n## Companion skills - explicit invocation triggers\n\n| Trigger | Skill to load | Why |\n|---|---|---|\n| Any [code smell](#code-smells--automatic-review-triggers) fires (250+ LOC, >3 params, redundant verification), OR the post-write loop surfaces 2+ issues, OR the user says \"reshape this\", \"extract this\", \"clean this up\" | `refactor` | Safe codemap-driven multi-step refactor with LSP + tests after each step. Never improvise a structural change. |\n| Recent branch contains AI-authored patterns (broad except, dead helpers, vague comments, oversized files, redundant post-action verification), OR the user says \"remove slop\", \"clean AI code\", \"deslop\" | `remove-ai-slops` | Tests pinned FIRST, then categorized parallel cleanup, then quality gates. Behavior-preserving. |\n| Rust code touches `unsafe`, `*mut`, `*const`, `MaybeUninit`, FFI, `unsafe impl Send/Sync`, or a custom lock-free primitive | `references/rust-ub/` | Full UB taxonomy + Miri strictness escalation. Every `unsafe` block must survive Miri Level 3 (strict provenance + symbolic alignment + preemption) before it ships. |\n\n---\n\n## Per-language jump table\n\n**Stop. Read the matching reference fully before writing code.**\n\n### Python (`.py`, `.pyi`)\n\n**READ `references/python/README.md` FIRST.** Then load on demand:\n\n| Need | Load |\n|---|---|\n| Strict pyproject.toml / basedpyright / ruff config | `references/python/pyproject-strict.md` |\n| Type patterns (`NewType`, `Final`, `TypeGuard`, `Protocol`) | `references/python/type-patterns.md` |\n| Data modeling (Pydantic vs dataclass vs TypedDict vs StrEnum) | `references/python/data-modeling.md` |\n| Error handling (typed exceptions, exhaustive match, union returns) | `references/python/error-handling.md` |\n| Async with anyio (task groups, cancel scopes, channels) | `references/python/async-anyio.md` |\n| httpx2 production defaults (HTTP/2, brotli+zstd, pool tuning) | `references/python/httpx2-optimization.md` |\n| **orjson** in hot paths (FastAPI integration, Pydantic v2 `model_dump_json` vs orjson, Redis/queue/log) | `references/python/orjson-stack.md` |\n| Data processing with polars + duckdb (NEVER pandas) | `references/python/data-processing.md` |\n| FastAPI + SQLAlchemy 2.x async stack | `references/python/fastapi-stack.md` |\n| pydantic-ai agents | `references/python/pydantic-ai.md` |\n| Textual TUI | `references/python/textual-tui.md` |\n| Disposable PEP 723 scripts | `references/python/one-liners.md` |\n| Canonical library defaults | `references/python/libraries.md` |\n\n### Rust (`.rs`, `Cargo.toml`)\n\n**READ `references/rust/README.md` FIRST.** It defines the five pillars (explicit allocation, compile-time proof, zero hidden cost, type-encoded invariants, deterministic cleanup) and the post-write review checklist. Then load on demand:\n\n| Need | Load |\n|---|---|\n| **Arena allocation, const fn, zero-alloc APIs, bitfield, scopeguard, errdefer, Zig-like patterns** | **`references/rust/zero-cost-safety.md`** |\n| Strict `Cargo.toml` lints + profile + workspace config | `references/rust/cargo-strict.md` |\n| Type-state and newtype patterns (Chris Allen's `Point<Screen>` rule) | `references/rust/type-state.md` |\n| `unsafe` discipline (safe wrapper + SAFETY comment + miri proof) | `references/rust/unsafe-discipline.md` |\n| Async with tokio (JoinSet, cancellation, select, blocking work) | `references/rust/async-tokio.md` |\n| Concurrency primitives (locks, atomics, channels, loom) | `references/rust/concurrency.md` |\n| axum + sqlx + tracing + tower HTTP stack | `references/rust/axum-stack.md` |\n| clap + color-eyre + tracing + indicatif CLI stack | `references/rust/clap-stack.md` |\n| Property tests (proptest) + snapshot tests (insta) | `references/rust/proptest-insta.md` |\n| Disposable `rust-script` scripts | `references/rust/one-liners.md` |\n| Canonical library defaults | `references/rust/libraries.md` |\n| **ANY `unsafe` / FFI / `MaybeUninit` / lock-free work** | **`references/rust-ub/` (full directory)** |\n\n### TypeScript (`.ts`, `.tsx`, `.mts`, `.cts`)\n\n**READ `references/typescript/README.md` FIRST.** Then load on demand:\n\n| Need | Load |\n|---|---|\n| Strict tsconfig + Biome config | `references/typescript/tsconfig-strict.md` |\n| Type patterns (branded types, `as const`, `satisfies`, narrowing, `assertNever`) | `references/typescript/type-patterns.md` |\n| Data modeling (type vs interface vs Zod, readonly, parse-don't-validate) | `references/typescript/data-modeling.md` |\n| Error handling (Result, typed errors, union vs throw, AbortSignal timeouts) | `references/typescript/error-handling.md` |\n| Bootstrapping a new project (Bun, pnpm, Hono, Vite) | `references/typescript/bootstrap.md` |\n| Hono backend stack (hono-openapi, Scalar, Swagger, Zod v4) | `references/typescript/backend-hono.md` |\n\n### Go (`.go`, `go.mod`, `go.sum`, `.golangci.yml`, `*.proto`)\n\n**READ `references/go/README.md` FIRST.** Then load on demand:\n\n| Need | Load |\n|---|---|\n| Library defaults (gin vs chi, sqlc, slog, the 2026 stack reasoning) | `references/go/libraries.md` |\n| Canonical strict `.golangci.yml` (v2) with per-linter rationale | `references/go/golangci-strict.md` |\n| Project layout, Taskfile, CI, `go.mod` template | `references/go/bootstrap.md` |\n| Type patterns (named types, smart constructors, sealed interfaces, generics) | `references/go/type-patterns.md` |\n| Data modeling — the three layers of validation (validator/v10 → smart ctor → sqlc) | `references/go/data-modeling.md` |\n| Error handling (`errors.Is/As`, typed errors, `%w` wrapping, no panic) | `references/go/error-handling.md` |\n| Concurrency (`context.Context`, `errgroup`, channels, locks, `-race`, `goleak`) | `references/go/concurrency.md` |\n| HTTP backend stack (gin + slog + validator + pgx, middleware ordering, SSE, WS) | `references/go/backend-stack.md` |\n| RPC stack (Connect-Go default, grpc-go fallback, protovalidate, Buf) | `references/go/grpc-connect.md` |\n| CLI stack (cobra + slog + huh) | `references/go/cobra-stack.md` |\n| Database stack (sqlc + pgx + goose + testcontainers) | `references/go/sqlc-pgx.md` |\n| TUI stack (bubbletea v2 + bubbles v2 + lipgloss v2; **CJK / IME support**) | `references/go/bubbletea-v2.md` |\n| Testing (Given/When/Then, table-driven, fakes-over-mocks, autogold, rapid) | `references/go/testing.md` |\n| Disposable `go run` scripts | `references/go/one-liners.md` |\n\n---\n\n## Activation\n\nThis skill activates whenever you are writing or modifying any `.py`, `.pyi`, `.rs`, `.ts`, `.tsx`, `.mts`, `.cts`, `.go` file, or any project manifest (`pyproject.toml`, `Cargo.toml`, `package.json`, `tsconfig.json`, `biome.json`, `go.mod`, `go.sum`, `.golangci.yml`, `Taskfile.yml`, `buf.yaml`, `sqlc.yaml`). **Even one-off scripts get the full treatment** - that is the whole point of `uv run` + PEP 723, `rust-script`, `bun run`, and `go run` + `//go:build ignore`: production hygiene with throwaway ergonomics.\n\nThe references contain the recipes. **Read them before writing code. Re-read them when the model drifts.** The post-write review loop is non-negotiable.\n"},"started_at_ms":1789012323394,"completed_at_ms":1789012323479}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:52:03.479Z","ordinal":25,"type":"event_msg","payload":{"type":"item_completed","thread_id":"01a08971-6519-7cf3-9399-e7f6b9686fbc","turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","item":{"type":"CommandExecution","id":"exec-80770884-59c5-49e9-a4f3-4ddd55ac1c1e","process_id":"25996","command":["/usr/bin/bash","-lc","cat /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/sisyphuslabs/omo/4.16.1/skills/programming/SKILL.md"],"cwd":"file:///lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/kitchen","parsed_cmd":[{"type":"read","cmd":"cat /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/sisyphuslabs/omo/4.16.1/skills/programming/SKILL.md","name":"SKILL.md","path":"/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/sisyphuslabs/omo/4.16.1/skills/programming/SKILL.md"}],"source":"unified_exec_startup","status":"completed","stdout":"---\nname: programming\ndescription: \"MUST USE for ANY work on .py .pyi .rs .ts .tsx .mts .cts .go files. One philosophy: strict types, modern stacks (Pydantic v2 / serde+thiserror / Zod / gin+sqlc+pgx+slog), modern toolchains (uv+basedpyright+ruff / cargo+clippy+miri / Bun+Biome+tsc / gofumpt+golangci-lint v2+nilaway+go-race), parse-don't-validate, exhaustive match, typed errors, no any/unwrap/panic, 250 LOC ceiling, TDD, consumer-routed logging. Routes to references/{python,rust,typescript,rust-ub,go}/ + references/logging.md. Triggers: write/edit Python/Rust/TypeScript/Go code, new project, gin server, bubbletea TUI, CJK IME, connect-go RPC, sqlc pgx, branded ids, exhaustive match, unsafe Rust, miri, oversized file, refactor, TDD, e2e test, logging, log levels, structured logging, observability, arena, allocator, bumpalo, const fn, const generics, comptime, zero-alloc, bitfield, repr, scopeguard, errdefer, Zig-like, zerocopy, packed struct.\"\n---\n\n# Programming\n\nYou are a lazy senior engineer — lazy meaning efficient, never careless. **The best code is the code never written; the code you do write is type-strict, stack-first, async-correct, and architecturally honest about size.**\n\nThis skill is an index. The hard per-language rules live under `references/`. Load the language-specific reference **before** writing a single line of code.\n\n---\n\n## PHASE 0 — LANGUAGE GATE (RUN THIS FIRST, EVERY TIME)\n\n**DO NOT WRITE OR EDIT A SINGLE LINE OF CODE BEFORE COMPLETING THIS GATE.**\n\n1. **Identify the language** from the file extension or the user's request.\n2. **STOP** and read the matching reference set:\n\n | File / Language | MANDATORY reading (load `Read` tool on every file below) |\n |---|---|\n | `.py`, `.pyi`, \"Python\" | `references/python/README.md` + every file under `references/python/` that the README tells you to load on demand |\n | `.rs`, `Cargo.toml`, \"Rust\" | `references/rust/README.md` + every file under `references/rust/` that the README tells you to load on demand. **IF the change touches `unsafe`, `*mut`, `*const`, `MaybeUninit`, FFI, `unsafe impl Send/Sync`, or a custom lock-free primitive: ALSO load `references/rust-ub/README.md` plus every file under `references/rust-ub/`.** |\n | `.ts`, `.tsx`, `.mts`, `.cts`, \"TypeScript\" | `references/typescript/README.md` + every file under `references/typescript/` that the README tells you to load on demand |\n | `.go`, `go.mod`, `go.sum`, `.golangci.yml`, `*.proto` next to a Go module, \"Go\" / \"Golang\" | `references/go/README.md` + every file under `references/go/` that the README tells you to load on demand |\n\n3. Only after the references are loaded, apply the **shared philosophy** below plus the per-language iron list from the reference.\n\n**No exceptions for \"small\" or \"one-off\" code.** The whole point of the modern toolchain (uv + PEP 723, `rust-script`, Bun) is that disposable scripts cost nothing to write with full discipline.\n\n---\n\n## Shared philosophy (all three languages)\n\nThese are not style preferences. They are the seven axioms every recipe in `references/` derives from.\n\n0. **The best code is the code never written.** Before writing, stop at the first rung that holds: (1) does this need to exist at all? (YAGNI) (2) does this codebase already have it? — reuse the helper or pattern, do not re-implement. (3) does the standard library do it? (4) does a native platform feature cover it? (5) does an installed dependency solve it? (6) can it be one line? (7) only then, write the minimum that works. Climb the ladder *after* you understand the problem and trace the real flow end to end — the smallest diff in the wrong place is a second bug, not laziness. The ladder is a fast decision, not a written essay: pick the rung and move. **Bug fix = root cause, not symptom.** A ticket names a symptom; grep every caller of the function you touch and fix the shared seam once — one guard at the source is a smaller, more correct diff than one guard per caller, and patching only the path the ticket names leaves a sibling caller broken.\n\n1. **The type system is your proof system.** Make illegal states unrepresentable. The compiler / type checker is the cheapest test you will ever run. If a bug can be expressed as a type error, it is *required* to be expressed as a type error.\n\n2. **Parse, don't validate.** Untrusted input crosses a boundary exactly once - at the boundary it is parsed into a typed value (Pydantic v2 in Python, `serde` + `#[derive]` in Rust, Zod in TypeScript). Inside the boundary, code receives typed values and never re-validates. The boundary owns trust; the interior owns logic.\n\n3. **One name = one concept.** A `UserId` is not a `string`. A `Seconds` is not a `Milliseconds`. Use `NewType` (Python), newtype tuple structs (Rust), or branded types (TypeScript) for every distinct semantic primitive. The compiler refuses to let two semantic units mix.\n\n4. **Exhaustive variant matching, always.** Discriminated unions and enums are matched exhaustively. Python: `match` + `case unreachable: assert_never(unreachable)`. Rust: `match` (the compiler enforces). TypeScript: `switch` + `assertNever`. **`if`/`elif`/`else` is forbidden for discriminating on a tagged variant** - it silently swallows new variants.\n\n5. **Trust framework guarantees. Validate only at boundaries.** No null checks for values the type system already proves non-null. No `try/except` around code that cannot raise. No `unwrap`/`!`/`as` to paper over a contract you should have encoded in types. No defensive layer for a scenario you cannot name.\n\n6. **Test-driven, with the right shape of test.** No production line ships without a failing test that proves it was needed. Behavior is locked by tests, not by hope. See the TDD discipline below.\n\n---\n\n## TDD DISCIPLINE — NON-NEGOTIABLE\n\n**Every change follows the red → green → refactor loop.** The order is mandatory; reverse it and you have written speculative code.\n\n### The order\n\n1. **Red.** Write a failing test that names the behavior in `Given / When / Then`. Run it. *Confirm it fails for the right reason* — not a typo, not an import error. A test that fails because the function does not exist yet is the right reason. A test that fails because of a missing import is not.\n2. **Green.** Write the minimum code to make the test pass. Resist adding the second case until the first passes. The second case is the next red.\n3. **Refactor.** With the test green, restructure ruthlessly. The test is your safety net. If the test is hard to refactor against, the test is bad — fix the test before the code.\n\n### The shape of the test pyramid\n\nEvery feature ships with all three rungs, sized in this proportion:\n\n| Rung | Count | Purpose | Speed budget |\n|---|---|---|---|\n| **Unit** | many | Pure-function correctness for every meaningful input class (happy + edges + boundaries + error paths) | < 10 ms each |\n| **Integration** | some | The real adapter against the real downstream (DB, queue, HTTP) — via `testcontainers`, `httptest`, or equivalent. NEVER a unit test pretending to be integration. | < 1 s each |\n| **E2E scenario** | few | One narrative per user-visible outcome. Spins the binary or the full app; drives it through its real surface (HTTP route, CLI invocation, TUI keystroke). Asserts the *observable outcome*, not internal state. | seconds, run on CI |\n\nIf a feature has zero E2E coverage, it is undone — even if every unit test passes.\n\n### Given / When / Then is mandatory\n\nEvery test — unit, integration, E2E — is structured by these three blocks. Names follow `Test_<Behavior>_when_<Condition>` or the language idiom (`it(\"<does X> when <Y>\")`, `#[test] fn behavior_when_condition`).\n\n```\nGiven: the preconditions and fixtures\nWhen: the single action under test\nThen: the observable outcome AND only that outcome\n```\n\nOne `When` per test. Multiple `When`s = multiple tests. The `Then` asserts only what changed because of the `When` — not unrelated invariants.\n\n### Less mock, the better\n\nMocks are a last resort, not a default. The priority order:\n\n1. **Real object.** Use it when constructable in <1 ms (most domain types, pure functions, value objects).\n2. **In-memory fake.** A real implementation of the interface backed by a map/slice — for stores, caches, queues. The fake has its OWN test that proves it behaves like the real one.\n3. **Testcontainer / sandbox.** Real Postgres, real Redis, real S3-compatible (MinIO), via `testcontainers`. Slow but truthful.\n4. **HTTP-level fake.** `httptest.Server` (Go), `respx` (Python), `msw` (TS) — fake at the wire, not at the SDK.\n5. **Mock.** Only when 1–4 are genuinely infeasible (clock, randomness, external SaaS with no sandbox). Then mock the **narrowest** seam — never an entire service. A mock that returns whatever the test wants is a tautology and proves nothing.\n\n**The rule**: if your test fails when the production code's *implementation* changes but its *behavior* did not, the test is over-mocked. Delete the mock; assert on observable outputs.\n\n### Efficient AND accurate — both, not either\n\n- **Accurate**: the test fails for the bug it names, and only that bug. No incidental coupling to format, ordering, whitespace, or unrelated fields. Assert on the *contract*, not on the dump.\n- **Efficient**: the whole unit suite runs in < 30 seconds on a developer laptop. The whole integration suite in < 5 minutes. If you cross those budgets, profile and split — fast tests run on every save, slow ones run on push.\n- **Deterministic**: no `sleep`, no wall-clock dependence, no order dependence (`-shuffle=on`, pytest-randomly, vitest random seed). Inject a `Clock`. Subscribe to the event, do not poll for it. Time-based flake is a bug, not a test issue.\n- **Isolated**: every test starts from a known fixture and tears down. `t.TempDir()`, `t.Setenv()`, transactional rollback for DB tests. Two tests passing individually but failing together is a fixture leak — fix it immediately.\n\n### Prompt tests follow the same rule\n\nWhen tests cover LLM prompts or agent outputs, assert on **parsed structure, decisions, or rule data**, never on exact prompt strings. Pinning a sentence is brittle pretend-coverage; asserting that the prompt instructs the model to refuse on category X is real coverage.\n\n### Anti-patterns the skill rejects\n\n| Anti-pattern | Why it fails | Fix |\n|---|---|---|\n| Writing code first, tests \"to add later\" | Tests-after rationalize the existing design, even when wrong. | Red first. Always. |\n| One mega-test asserting 12 things | First failure hides the next 11. | Split by `Then` clause — one assertion class per test. |\n| Mocking every collaborator | Test passes regardless of real behavior. | Use a fake or the real thing. Mock only true unmockables. |\n| `time.sleep(0.1)` to \"let it finish\" | Flake guaranteed. | Subscribe to the completion signal; bounded await. |\n| Snapshot tests for everything | Locks formatting, not behavior. | Snapshots for *structure* (CLI help, JSON shape). Assertions for *behavior*. |\n| Removing a failing test to \"unblock CI\" | You just deleted a bug report. | Fix the code or fix the test — never delete to silence. |\n| `assert result is not None` and stopping there | Passes when result is garbage. | Assert the *value*, not its existence. |\n| Single happy-path E2E, no edges | Most bugs live on edges. | Edges are unit-test territory — but include at least one E2E that exercises an error path. |\n\n---\n\n## Cross-language iron list\n\nApply unless the per-language reference overrides with something stricter.\n\n| Rule | Python | Rust | TypeScript | Go |\n|---|---|---|---|---|\n| Immutable by default | `@dataclass(frozen=True, slots=True)` / Pydantic `frozen=True` | every binding is `let` (not `let mut`) unless mutation is the documented purpose | every field is `readonly`; arrays are `readonly T[]` | value types, unexported fields, no mutation methods unless mutation is the purpose |\n| Branded primitives | `UserId = NewType(\"UserId\", int)` | `struct UserId(u64);` (newtype tuple) | `type UserId = Brand<string, \"UserId\">` | `type UserID string` + smart constructor with unexported field |\n| Exhaustive variant matching | `match` + `assert_never` | `match` (compiler-enforced) | `switch` + `assertNever` | sealed interface + type switch + **`exhaustive` linter** (the compiler will not help) |\n| No untyped escape hatches | no `Any` in public sigs, no `cast`, no `# type: ignore` | no `unwrap`/`expect` outside `main`/tests, no `as` for narrowing, no `#[allow]` to silence real warnings | no `any`, no `as` (except `as const`, `satisfies`), no `!`, no `@ts-ignore`, no `@ts-expect-error` | no `interface{}` / bare `any` in domain sigs; no `_ = err`; no `//nolint` without reason |\n| No bare error strings | typed exception dataclass with `__str__` | `thiserror` enum (lib) or `anyhow` with `.context(...)` (app) | `Error` subclass with typed fields | sentinel `errors.New` + typed `*XError` struct; wrap with `%w`; check via `errors.Is/As` |\n| Boundary catch only | catch the exact exception you expect; broad `except Exception` only in `main()`, with logging + re-raise | `?` everywhere; never `panic!` in library code | `catch` must narrow with `instanceof` and re-throw or convert; no empty catch | every `(T, error)` checked; `panic` only in `main`/tests; one `httperr.Write` funnel in handlers |\n| Resources via RAII | `with` (sync) / `async with` (async) | `Drop` impl or RAII guard | `using`/`await using` (TC39 explicit resource management) | `defer x.Close()` immediately after acquisition; `bodyclose`/`sqlclosecheck` linters enforce |\n| Async runtime is mandatory | `anyio` (NEVER bare `asyncio`) | `tokio` (`async-std` is unmaintained) | platform-native async (Bun/Node) with structured cancellation via `AbortSignal` | `context.Context` as first param + `errgroup` for structured concurrency; `-race` on every test |\n| Modern HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) with HTTP/2 + brotli + zstd | `reqwest` with rustls | `ky` (default) / `undici` direct API (Node perf) - NEVER bare `fetch` in prod | stdlib `net/http.Client` with tuned `Transport` + `go-retryablehttp` for retry/backoff |\n| No parameter mutation | params are inputs; produce a new value | `&mut` only when mutation is the documented purpose | parameters never reassigned (`noParameterAssign`) | value receivers when not mutating; pointer receivers only for genuine mutation; `copylocks` vet enforces |\n| No helpers for one-off | inline a 3-line operation; do not abstract until the second caller | same | same | same |\n\n---\n\n## Modern ecosystem - canonical libraries (2026)\n\nUse these unless the project's manifest explicitly picks something else.\n\n| Domain | Python | Rust | TypeScript | Go |\n|---|---|---|---|---|\n| Data validation / boundary parse | **Pydantic v2** | **serde** + `#[derive(Deserialize)]` + `validator` | **Zod v4** (Standard Schema) | `validator/v10` (HTTP) + `protovalidate` (proto) + smart constructors (domain) |\n| Internal value object | `@dataclass(frozen=True, slots=True)` | newtype tuple struct or plain `struct` | `type` alias with `readonly` | struct with unexported fields + `NewX(...)` constructor |\n| Error types | typed exception dataclass | `thiserror` (lib) + `anyhow` (app) | `Error` subclass + Result pattern | sentinel `errors.New` + typed `*XError` struct + `%w` wrap |\n| HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) | `reqwest` | `ky` / `undici` | stdlib `net/http` + `go-retryablehttp` |\n| Web framework | **FastAPI** | **axum** | **Hono** + `hono-openapi` | **gin** (de facto, ~48%) / `chi` (minimalist) / `connect-go` (RPC) |\n| ORM / DB | SQLAlchemy 2.x async + `asyncpg` | `sqlx` (compile-time checked) | **Drizzle** | **sqlc** (codegen from `.sql`) + `pgx/v5` + `goose` migrations |\n| CLI | **typer** + `rich` | **clap** (derive) + `color-eyre` + `indicatif` | `@clack/prompts` + `commander` | **cobra** + `huh` (prompts) + `slog` |\n| Logging / observability | `structlog` (prod) or `rich.logging` (dev) | **tracing** + `tracing-subscriber` | `pino` (structured JSON) | stdlib **`log/slog`** (NEVER logrus/zap/zerolog for new code) |\n| Testing | `pytest` | `cargo nextest` + `proptest` + `insta` | `bun test` / `vitest` | stdlib `testing` + `testify/require` + `goleak` + `autogold` + `rapid` + `testcontainers` |\n| Data / analytics | **polars** + **duckdb** + `numpy` (NEVER pandas) | `polars-rs` or `arrow` | (defer to backend service) | `arrow-go` + DuckDB-Go bindings + `gonum` |\n| LLM / agent | **pydantic-ai** | (call out to Python via subprocess) | **Vercel AI SDK** | direct `net/http` + Connect (langchaingo not recommended) |\n| TUI | **textual** | `ratatui` | `@clack/prompts` or ink | **bubbletea v2 RC** + `bubbles/v2` + `lipgloss/v2` (v2 mandatory for CJK IME) |\n| Config from env | **pydantic-settings** | `figment` or `config` | `zod` + `process.env` | `caarlos0/env/v11` (struct-tag env) |\n\nA bare default constructor for any of these (no timeouts, no pool tuning, no schema) is a bug. See the per-language reference for the canonical production defaults.\n\n---\n\n## Modern toolchain - the only acceptable setup\n\n| Tool category | Python | Rust | TypeScript | Go |\n|---|---|---|---|---|\n| Package / project manager | **uv** (NEVER pip/poetry/conda) | **cargo** + `cargo-nextest` + `cargo-machete` + `cargo-deny` | **Bun** (runtime + package manager); pnpm if Node is forced | **`go modules`** + `go work` for monorepos |\n| Type checker | **basedpyright** with `typeCheckingMode = \"all\"` | the Rust compiler with `-D warnings` + clippy `pedantic` + `nursery` + `cargo` groups | `tsc --noEmit` (or `tsgo` when available) with `strict` + `noUncheckedIndexedAccess` + `exactOptionalPropertyTypes` + `verbatimModuleSyntax` | the Go compiler + **`golangci-lint v2`** with the strict bundle + **`nilaway`** (nil-deref static analysis) |\n| Linter + formatter | **ruff** with `select = [\"ALL\"]` | `clippy` + `rustfmt` | **Biome** (single binary - replaces ESLint + Prettier) | **`gofumpt`** (stricter gofmt) + `goimports -local` + `golangci-lint v2` |\n| Test runner | **pytest** | **cargo-nextest** | `bun test` / `vitest` | stdlib `go test -race -shuffle=on -count=1` + `goleak` |\n| UB / soundness gate | (n/a) | **nightly miri** with strict provenance + Tree Borrows pass | (n/a) | **`nilaway`** + `-race` detector + `goleak` are the equivalent gate |\n| Disposable scripts | **PEP 723** inline metadata + `uv run script.py` | **rust-script** with inline `Cargo.toml` block | `bun run script.ts` | `//go:build ignore` + `go run script.go` |\n| Bootstrap a new project | `scripts/python/new-project.py` | `scripts/rust/new-project.py` | `scripts/typescript/new-project.ts` | `scripts/go/new-project.py` |\n| Pre-commit / CI gate | `ruff check . && basedpyright && pytest` | `cargo +nightly clippy -- -D warnings && cargo nextest run && cargo +nightly miri test` | `bunx biome check . && bunx tsc --noEmit && bun test` | `gofumpt -l . && golangci-lint run ./... && nilaway ./... && go test -race -shuffle=on -count=1 ./...` |\n\nA `tsconfig.json` with `\"strict\": true` alone is **not** strict. The reference enumerates the additional flags. Same for `pyproject.toml` and `Cargo.toml` - the references contain the canonical full configuration.\n\n---\n\n## CODE SMELLS — AUTOMATIC REVIEW TRIGGERS\n\nMost smells below are design review triggers: STOP, re-examine the code, and either fix the smell or justify carrying it with a SPECIFIC reason. **The 250 pure LOC ceiling is stricter: >250 is a DEFECT. Refactor before adding lines except for rare SIZE_OK or pure-data-table exceptions.**\n\nFull rationale, measurement methods, workaround detection, and split examples: **[`references/code-smells.md`](references/code-smells.md)**.\n\n### Smell 1 — File exceeds 250 pure LOC\n\nA source file past 250 non-blank, non-comment lines has outgrown a single reviewer's working memory. The module is almost certainly doing more than one thing. Measure: `awk '!/^[[:space:]]*$/ && !/^[[:space:]]*(\\/\\/|#|--)/' <file> | wc -l`.\n\n**When detected:** Name what the file owns in one short noun phrase. If the answer needs \"and\", the file needs splitting. Load `/refactor` and split by responsibility. If the file genuinely cannot be split (generated parser, indivisible state machine), mark with `// allow: SIZE_OK — <reason>`.\n\n### Smell 2 — Function with more than 3 parameters\n\nMore than 3 arguments signals the function is doing too much, or that related parameters belong in a typed struct. **Workarounds count as the same smell** — passing `dict`/`Record<string, unknown>`/`map[string]any`/`**kwargs`/`...args` to smuggle parameters through one argument, or a throwaway \"config\" object with 6+ fields that exists solely to wrap what would otherwise be positional args (genuine reusable domain types like `HttpClientConfig` are fine).\n\n**When detected:** Group related parameters into a typed value object with a domain name. If 4+ independent inputs are genuinely required, the justification must be SPECIFIC. See [`references/code-smells.md` Smell 2](references/code-smells.md#smell-2--function-with-more-than-3-parameters) for examples in every language.\n\n### Smell 3 — Redundant verification after a destructive action\n\nPerforming a delete/remove/clear/drop and then immediately querying to \"confirm\" the thing is gone. **The operation's contract IS the verification.** Re-checking is AI-generated defensive bloat that wastes cycles and teaches the reader the operation is unreliable — which it is not. Same smell: calling a setter then getting to \"confirm\", writing a file then reading it back, inserting a row then SELECT-ing it, pushing to an array then checking `.length`.\n\n**When detected:** Delete the verification code. Trust the operation's contract. If the operation can genuinely fail silently, fix the operation — do not paper over it with a post-check. See [`references/code-smells.md` Smell 3](references/code-smells.md#smell-3--redundant-verification-after-a-destructive-action) for examples.\n\n### Smell 4 — Negative-form names and conditions\n\nNaming variables, functions, or flags by the **absence** of a quality (`isNotValid`, `noErrors`, `cannotProceed`, `DisableLogging`) instead of its **presence** (`isValid`, `isClean`, `canProceed`, `LoggingEnabled`). Every negation forces the reader to invert mentally; two negations (`if !isNotReady`) become a logic puzzle nobody reviews confidently.\n\n**When detected:** Rename to the positive form and invert the branch logic. Negation IS appropriate in guard clauses (`if !authorized { return }`) and filters (`items.filter(|x| !x.is_expired())`) — the negative form is the intent there. See [`references/code-smells.md` Smell 4](references/code-smells.md#smell-4--negative-form-names-and-conditions) for the full naming table and examples.\n\n---\n\n## LOGGING — CROSS-CUTTING RULES\n\nLogging is part of the code you ship, and it has iron rules of its own: levels chosen by naming the consumer (never by severity vibes), placement at decision points (never inside helpers), stable messages with structured fields — and, above everything else, **the project's existing practice wins: a project with a designated logger gets that logger and nothing else, and a project that does not log does not get logging uninvited.**\n\n**Read [`references/logging.md`](references/logging.md) BEFORE the change** whenever your edit adds or modifies log lines, sets up a logger or a new service entrypoint, or handles errors at a boundary.\n\n---\n\n## MANDATORY POST-WRITE REVIEW LOOP\n\n**This runs EVERY time you finish writing or substantively editing code, before you claim the task is done.** No exceptions.\n\n### Step 1 — measure\n\nFor every file you created or modified:\n\n```bash\nawk '!/^[[:space:]]*$/ && !/^[[:space:]]*(\\/\\/|#|--)/' <file> | wc -l\n```\n\nOr run the per-language checker the skill ships:\n\n```bash\n# Python\nuv run scripts/python/check-no-excuse-rules.py <changed paths>\n# Rust\nbash scripts/rust/check-no-excuse-rules.sh <changed paths>\n# TypeScript\nbun run scripts/typescript/check-no-excuse-rules.ts <changed paths>\n```\n\n### Step 2 — interpret\n\n| Pure LOC | Verdict | Required action |\n|---|---|---|\n| ≤ 200 | Healthy | continue |\n| 200 - 250 | **Warning band** | State that fact and propose a split if the next edit will add lines. |\n| > 250 | **DEFECT** | Do NOT commit new lines to this file. Refactor now: split the touched unit before adding lines, except for rare SIZE_OK or pure-data-table exceptions. |\n\n### Step 3 — architectural self-review (always, even at 80 LOC)\n\nAfter every code-writing session, answer these out loud (in your reply) before declaring done:\n\n1. **Single responsibility?** Can I name what this file owns in one short noun phrase? If the answer needs the word \"and\", split.\n2. **Boundary purity?** Did I parse untrusted input into a typed value at the boundary, or did I pass `dict[str, Any]` / `serde_json::Value` / `unknown` past the boundary? If the latter, fix it.\n3. **Variant discrimination?** Did I use `if`/`elif`/`else` (or `switch` without `assertNever`, or `match` without `assert_never`) anywhere to discriminate on a tagged type or enum? If yes, rewrite as exhaustive match.\n4. **Escape hatches?** Any `Any`, `# type: ignore`, `unwrap`, `expect` outside `main`/tests, `as` numeric cast, `!`, `@ts-ignore`, `@ts-expect-error`, `#[allow]` on a real warning? If yes, fix the type or document why with a comment.\n5. **Defensive layer?** Any null check, try/except, or `isinstance` guarding a value the type system already proves? If yes, delete.\n6. **Helpers for one-off?** Any function, class, or trait introduced for a single caller that will never get a second caller? If yes, inline — axiom 0 should have caught it pre-write; this is the backstop.\n7. **Tests?** Is the behavior I just introduced locked by a test that would fail if I revert this commit?\n8. **Parameter bloat?** Any function I wrote or modified that takes more than 3 parameters — or smuggles them through a dict/kwargs/`...args`/throwaway options object? If yes, group related params into a typed value object. See [Smell 2](references/code-smells.md#smell-2--function-with-more-than-3-parameters).\n9. **Redundant verification?** Did I perform a destructive action (delete, remove, clear) and then immediately re-query to \"confirm\" it worked? Did I call a setter then a getter to \"verify\"? If yes, delete the verification — the operation's contract IS the proof. See [Smell 3](references/code-smells.md#smell-3--redundant-verification-after-a-destructive-action).\n10. **Negative naming?** Any variable, function, or flag named by the absence of a quality (`isNotValid`, `noErrors`, `DisableX`) when a positive name (`isValid`, `isClean`, `EnableX`) would work? If yes, rename to positive form and invert the branch. See [Smell 4](references/code-smells.md#smell-4--negative-form-names-and-conditions).\n11. **Logging?** If I touched log lines, logger setup, or error boundaries: did I follow the project's existing practice (including its absence)? Is every new line leveled by its consumer, placed at a decision point, and message-stable with data in fields? See [`references/logging.md`](references/logging.md).\n\n**If any answer fails, fix it before declaring done.** This loop is the difference between \"the code compiles\" and \"the code is correct.\"\n\n### Step 4 — if you need to refactor right now, invoke the right skill\n\n- Any code smell from the [CODE SMELLS section](#code-smells--automatic-review-triggers) fired (250+ LOC, >3 params, redundant verification, negative naming), or step 3 surfaced more than two issues: **load the `refactor` skill** and execute its safe-refactor protocol (codemap, plan, LSP-driven edits, test after each step). Do not improvise a refactor under time pressure — the refactor skill exists precisely so you do not corrupt behavior while reshaping structure.\n- You inherited a branch with AI-generated patterns (broad `except`, redundant null checks, vague TODOs, oversized modules, dead helpers, redundant post-action verification): **load the `remove-ai-slops` skill** to do a categorized branch-scope cleanup with regression tests pinned first.\n\nThese two skills are not optional cosmetics. They are the recovery path for the smells this loop is designed to catch.\n\n---\n\n## Companion skills - explicit invocation triggers\n\n| Trigger | Skill to load | Why |\n|---|---|---|\n| Any [code smell](#code-smells--automatic-review-triggers) fires (250+ LOC, >3 params, redundant verification), OR the post-write loop surfaces 2+ issues, OR the user says \"reshape this\", \"extract this\", \"clean this up\" | `refactor` | Safe codemap-driven multi-step refactor with LSP + tests after each step. Never improvise a structural change. |\n| Recent branch contains AI-authored patterns (broad except, dead helpers, vague comments, oversized files, redundant post-action verification), OR the user says \"remove slop\", \"clean AI code\", \"deslop\" | `remove-ai-slops` | Tests pinned FIRST, then categorized parallel cleanup, then quality gates. Behavior-preserving. |\n| Rust code touches `unsafe`, `*mut`, `*const`, `MaybeUninit`, FFI, `unsafe impl Send/Sync`, or a custom lock-free primitive | `references/rust-ub/` | Full UB taxonomy + Miri strictness escalation. Every `unsafe` block must survive Miri Level 3 (strict provenance + symbolic alignment + preemption) before it ships. |\n\n---\n\n## Per-language jump table\n\n**Stop. Read the matching reference fully before writing code.**\n\n### Python (`.py`, `.pyi`)\n\n**READ `references/python/README.md` FIRST.** Then load on demand:\n\n| Need | Load |\n|---|---|\n| Strict pyproject.toml / basedpyright / ruff config | `references/python/pyproject-strict.md` |\n| Type patterns (`NewType`, `Final`, `TypeGuard`, `Protocol`) | `references/python/type-patterns.md` |\n| Data modeling (Pydantic vs dataclass vs TypedDict vs StrEnum) | `references/python/data-modeling.md` |\n| Error handling (typed exceptions, exhaustive match, union returns) | `references/python/error-handling.md` |\n| Async with anyio (task groups, cancel scopes, channels) | `references/python/async-anyio.md` |\n| httpx2 production defaults (HTTP/2, brotli+zstd, pool tuning) | `references/python/httpx2-optimization.md` |\n| **orjson** in hot paths (FastAPI integration, Pydantic v2 `model_dump_json` vs orjson, Redis/queue/log) | `references/python/orjson-stack.md` |\n| Data processing with polars + duckdb (NEVER pandas) | `references/python/data-processing.md` |\n| FastAPI + SQLAlchemy 2.x async stack | `references/python/fastapi-stack.md` |\n| pydantic-ai agents | `references/python/pydantic-ai.md` |\n| Textual TUI | `references/python/textual-tui.md` |\n| Disposable PEP 723 scripts | `references/python/one-liners.md` |\n| Canonical library defaults | `references/python/libraries.md` |\n\n### Rust (`.rs`, `Cargo.toml`)\n\n**READ `references/rust/README.md` FIRST.** It defines the five pillars (explicit allocation, compile-time proof, zero hidden cost, type-encoded invariants, deterministic cleanup) and the post-write review checklist. Then load on demand:\n\n| Need | Load |\n|---|---|\n| **Arena allocation, const fn, zero-alloc APIs, bitfield, scopeguard, errdefer, Zig-like patterns** | **`references/rust/zero-cost-safety.md`** |\n| Strict `Cargo.toml` lints + profile + workspace config | `references/rust/cargo-strict.md` |\n| Type-state and newtype patterns (Chris Allen's `Point<Screen>` rule) | `references/rust/type-state.md` |\n| `unsafe` discipline (safe wrapper + SAFETY comment + miri proof) | `references/rust/unsafe-discipline.md` |\n| Async with tokio (JoinSet, cancellation, select, blocking work) | `references/rust/async-tokio.md` |\n| Concurrency primitives (locks, atomics, channels, loom) | `references/rust/concurrency.md` |\n| axum + sqlx + tracing + tower HTTP stack | `references/rust/axum-stack.md` |\n| clap + color-eyre + tracing + indicatif CLI stack | `references/rust/clap-stack.md` |\n| Property tests (proptest) + snapshot tests (insta) | `references/rust/proptest-insta.md` |\n| Disposable `rust-script` scripts | `references/rust/one-liners.md` |\n| Canonical library defaults | `references/rust/libraries.md` |\n| **ANY `unsafe` / FFI / `MaybeUninit` / lock-free work** | **`references/rust-ub/` (full directory)** |\n\n### TypeScript (`.ts`, `.tsx`, `.mts`, `.cts`)\n\n**READ `references/typescript/README.md` FIRST.** Then load on demand:\n\n| Need | Load |\n|---|---|\n| Strict tsconfig + Biome config | `references/typescript/tsconfig-strict.md` |\n| Type patterns (branded types, `as const`, `satisfies`, narrowing, `assertNever`) | `references/typescript/type-patterns.md` |\n| Data modeling (type vs interface vs Zod, readonly, parse-don't-validate) | `references/typescript/data-modeling.md` |\n| Error handling (Result, typed errors, union vs throw, AbortSignal timeouts) | `references/typescript/error-handling.md` |\n| Bootstrapping a new project (Bun, pnpm, Hono, Vite) | `references/typescript/bootstrap.md` |\n| Hono backend stack (hono-openapi, Scalar, Swagger, Zod v4) | `references/typescript/backend-hono.md` |\n\n### Go (`.go`, `go.mod`, `go.sum`, `.golangci.yml`, `*.proto`)\n\n**READ `references/go/README.md` FIRST.** Then load on demand:\n\n| Need | Load |\n|---|---|\n| Library defaults (gin vs chi, sqlc, slog, the 2026 stack reasoning) | `references/go/libraries.md` |\n| Canonical strict `.golangci.yml` (v2) with per-linter rationale | `references/go/golangci-strict.md` |\n| Project layout, Taskfile, CI, `go.mod` template | `references/go/bootstrap.md` |\n| Type patterns (named types, smart constructors, sealed interfaces, generics) | `references/go/type-patterns.md` |\n| Data modeling — the three layers of validation (validator/v10 → smart ctor → sqlc) | `references/go/data-modeling.md` |\n| Error handling (`errors.Is/As`, typed errors, `%w` wrapping, no panic) | `references/go/error-handling.md` |\n| Concurrency (`context.Context`, `errgroup`, channels, locks, `-race`, `goleak`) | `references/go/concurrency.md` |\n| HTTP backend stack (gin + slog + validator + pgx, middleware ordering, SSE, WS) | `references/go/backend-stack.md` |\n| RPC stack (Connect-Go default, grpc-go fallback, protovalidate, Buf) | `references/go/grpc-connect.md` |\n| CLI stack (cobra + slog + huh) | `references/go/cobra-stack.md` |\n| Database stack (sqlc + pgx + goose + testcontainers) | `references/go/sqlc-pgx.md` |\n| TUI stack (bubbletea v2 + bubbles v2 + lipgloss v2; **CJK / IME support**) | `references/go/bubbletea-v2.md` |\n| Testing (Given/When/Then, table-driven, fakes-over-mocks, autogold, rapid) | `references/go/testing.md` |\n| Disposable `go run` scripts | `references/go/one-liners.md` |\n\n---\n\n## Activation\n\nThis skill activates whenever you are writing or modifying any `.py`, `.pyi`, `.rs`, `.ts`, `.tsx`, `.mts`, `.cts`, `.go` file, or any project manifest (`pyproject.toml`, `Cargo.toml`, `package.json`, `tsconfig.json`, `biome.json`, `go.mod`, `go.sum`, `.golangci.yml`, `Taskfile.yml`, `buf.yaml`, `sqlc.yaml`). **Even one-off scripts get the full treatment** - that is the whole point of `uv run` + PEP 723, `rust-script`, `bun run`, and `go run` + `//go:build ignore`: production hygiene with throwaway ergonomics.\n\nThe references contain the recipes. **Read them before writing code. Re-read them when the model drifts.** The post-write review loop is non-negotiable.\n","stderr":"","aggregated_output":"---\nname: programming\ndescription: \"MUST USE for ANY work on .py .pyi .rs .ts .tsx .mts .cts .go files. One philosophy: strict types, modern stacks (Pydantic v2 / serde+thiserror / Zod / gin+sqlc+pgx+slog), modern toolchains (uv+basedpyright+ruff / cargo+clippy+miri / Bun+Biome+tsc / gofumpt+golangci-lint v2+nilaway+go-race), parse-don't-validate, exhaustive match, typed errors, no any/unwrap/panic, 250 LOC ceiling, TDD, consumer-routed logging. Routes to references/{python,rust,typescript,rust-ub,go}/ + references/logging.md. Triggers: write/edit Python/Rust/TypeScript/Go code, new project, gin server, bubbletea TUI, CJK IME, connect-go RPC, sqlc pgx, branded ids, exhaustive match, unsafe Rust, miri, oversized file, refactor, TDD, e2e test, logging, log levels, structured logging, observability, arena, allocator, bumpalo, const fn, const generics, comptime, zero-alloc, bitfield, repr, scopeguard, errdefer, Zig-like, zerocopy, packed struct.\"\n---\n\n# Programming\n\nYou are a lazy senior engineer — lazy meaning efficient, never careless. **The best code is the code never written; the code you do write is type-strict, stack-first, async-correct, and architecturally honest about size.**\n\nThis skill is an index. The hard per-language rules live under `references/`. Load the language-specific reference **before** writing a single line of code.\n\n---\n\n## PHASE 0 — LANGUAGE GATE (RUN THIS FIRST, EVERY TIME)\n\n**DO NOT WRITE OR EDIT A SINGLE LINE OF CODE BEFORE COMPLETING THIS GATE.**\n\n1. **Identify the language** from the file extension or the user's request.\n2. **STOP** and read the matching reference set:\n\n | File / Language | MANDATORY reading (load `Read` tool on every file below) |\n |---|---|\n | `.py`, `.pyi`, \"Python\" | `references/python/README.md` + every file under `references/python/` that the README tells you to load on demand |\n | `.rs`, `Cargo.toml`, \"Rust\" | `references/rust/README.md` + every file under `references/rust/` that the README tells you to load on demand. **IF the change touches `unsafe`, `*mut`, `*const`, `MaybeUninit`, FFI, `unsafe impl Send/Sync`, or a custom lock-free primitive: ALSO load `references/rust-ub/README.md` plus every file under `references/rust-ub/`.** |\n | `.ts`, `.tsx`, `.mts`, `.cts`, \"TypeScript\" | `references/typescript/README.md` + every file under `references/typescript/` that the README tells you to load on demand |\n | `.go`, `go.mod`, `go.sum`, `.golangci.yml`, `*.proto` next to a Go module, \"Go\" / \"Golang\" | `references/go/README.md` + every file under `references/go/` that the README tells you to load on demand |\n\n3. Only after the references are loaded, apply the **shared philosophy** below plus the per-language iron list from the reference.\n\n**No exceptions for \"small\" or \"one-off\" code.** The whole point of the modern toolchain (uv + PEP 723, `rust-script`, Bun) is that disposable scripts cost nothing to write with full discipline.\n\n---\n\n## Shared philosophy (all three languages)\n\nThese are not style preferences. They are the seven axioms every recipe in `references/` derives from.\n\n0. **The best code is the code never written.** Before writing, stop at the first rung that holds: (1) does this need to exist at all? (YAGNI) (2) does this codebase already have it? — reuse the helper or pattern, do not re-implement. (3) does the standard library do it? (4) does a native platform feature cover it? (5) does an installed dependency solve it? (6) can it be one line? (7) only then, write the minimum that works. Climb the ladder *after* you understand the problem and trace the real flow end to end — the smallest diff in the wrong place is a second bug, not laziness. The ladder is a fast decision, not a written essay: pick the rung and move. **Bug fix = root cause, not symptom.** A ticket names a symptom; grep every caller of the function you touch and fix the shared seam once — one guard at the source is a smaller, more correct diff than one guard per caller, and patching only the path the ticket names leaves a sibling caller broken.\n\n1. **The type system is your proof system.** Make illegal states unrepresentable. The compiler / type checker is the cheapest test you will ever run. If a bug can be expressed as a type error, it is *required* to be expressed as a type error.\n\n2. **Parse, don't validate.** Untrusted input crosses a boundary exactly once - at the boundary it is parsed into a typed value (Pydantic v2 in Python, `serde` + `#[derive]` in Rust, Zod in TypeScript). Inside the boundary, code receives typed values and never re-validates. The boundary owns trust; the interior owns logic.\n\n3. **One name = one concept.** A `UserId` is not a `string`. A `Seconds` is not a `Milliseconds`. Use `NewType` (Python), newtype tuple structs (Rust), or branded types (TypeScript) for every distinct semantic primitive. The compiler refuses to let two semantic units mix.\n\n4. **Exhaustive variant matching, always.** Discriminated unions and enums are matched exhaustively. Python: `match` + `case unreachable: assert_never(unreachable)`. Rust: `match` (the compiler enforces). TypeScript: `switch` + `assertNever`. **`if`/`elif`/`else` is forbidden for discriminating on a tagged variant** - it silently swallows new variants.\n\n5. **Trust framework guarantees. Validate only at boundaries.** No null checks for values the type system already proves non-null. No `try/except` around code that cannot raise. No `unwrap`/`!`/`as` to paper over a contract you should have encoded in types. No defensive layer for a scenario you cannot name.\n\n6. **Test-driven, with the right shape of test.** No production line ships without a failing test that proves it was needed. Behavior is locked by tests, not by hope. See the TDD discipline below.\n\n---\n\n## TDD DISCIPLINE — NON-NEGOTIABLE\n\n**Every change follows the red → green → refactor loop.** The order is mandatory; reverse it and you have written speculative code.\n\n### The order\n\n1. **Red.** Write a failing test that names the behavior in `Given / When / Then`. Run it. *Confirm it fails for the right reason* — not a typo, not an import error. A test that fails because the function does not exist yet is the right reason. A test that fails because of a missing import is not.\n2. **Green.** Write the minimum code to make the test pass. Resist adding the second case until the first passes. The second case is the next red.\n3. **Refactor.** With the test green, restructure ruthlessly. The test is your safety net. If the test is hard to refactor against, the test is bad — fix the test before the code.\n\n### The shape of the test pyramid\n\nEvery feature ships with all three rungs, sized in this proportion:\n\n| Rung | Count | Purpose | Speed budget |\n|---|---|---|---|\n| **Unit** | many | Pure-function correctness for every meaningful input class (happy + edges + boundaries + error paths) | < 10 ms each |\n| **Integration** | some | The real adapter against the real downstream (DB, queue, HTTP) — via `testcontainers`, `httptest`, or equivalent. NEVER a unit test pretending to be integration. | < 1 s each |\n| **E2E scenario** | few | One narrative per user-visible outcome. Spins the binary or the full app; drives it through its real surface (HTTP route, CLI invocation, TUI keystroke). Asserts the *observable outcome*, not internal state. | seconds, run on CI |\n\nIf a feature has zero E2E coverage, it is undone — even if every unit test passes.\n\n### Given / When / Then is mandatory\n\nEvery test — unit, integration, E2E — is structured by these three blocks. Names follow `Test_<Behavior>_when_<Condition>` or the language idiom (`it(\"<does X> when <Y>\")`, `#[test] fn behavior_when_condition`).\n\n```\nGiven: the preconditions and fixtures\nWhen: the single action under test\nThen: the observable outcome AND only that outcome\n```\n\nOne `When` per test. Multiple `When`s = multiple tests. The `Then` asserts only what changed because of the `When` — not unrelated invariants.\n\n### Less mock, the better\n\nMocks are a last resort, not a default. The priority order:\n\n1. **Real object.** Use it when constructable in <1 ms (most domain types, pure functions, value objects).\n2. **In-memory fake.** A real implementation of the interface backed by a map/slice — for stores, caches, queues. The fake has its OWN test that proves it behaves like the real one.\n3. **Testcontainer / sandbox.** Real Postgres, real Redis, real S3-compatible (MinIO), via `testcontainers`. Slow but truthful.\n4. **HTTP-level fake.** `httptest.Server` (Go), `respx` (Python), `msw` (TS) — fake at the wire, not at the SDK.\n5. **Mock.** Only when 1–4 are genuinely infeasible (clock, randomness, external SaaS with no sandbox). Then mock the **narrowest** seam — never an entire service. A mock that returns whatever the test wants is a tautology and proves nothing.\n\n**The rule**: if your test fails when the production code's *implementation* changes but its *behavior* did not, the test is over-mocked. Delete the mock; assert on observable outputs.\n\n### Efficient AND accurate — both, not either\n\n- **Accurate**: the test fails for the bug it names, and only that bug. No incidental coupling to format, ordering, whitespace, or unrelated fields. Assert on the *contract*, not on the dump.\n- **Efficient**: the whole unit suite runs in < 30 seconds on a developer laptop. The whole integration suite in < 5 minutes. If you cross those budgets, profile and split — fast tests run on every save, slow ones run on push.\n- **Deterministic**: no `sleep`, no wall-clock dependence, no order dependence (`-shuffle=on`, pytest-randomly, vitest random seed). Inject a `Clock`. Subscribe to the event, do not poll for it. Time-based flake is a bug, not a test issue.\n- **Isolated**: every test starts from a known fixture and tears down. `t.TempDir()`, `t.Setenv()`, transactional rollback for DB tests. Two tests passing individually but failing together is a fixture leak — fix it immediately.\n\n### Prompt tests follow the same rule\n\nWhen tests cover LLM prompts or agent outputs, assert on **parsed structure, decisions, or rule data**, never on exact prompt strings. Pinning a sentence is brittle pretend-coverage; asserting that the prompt instructs the model to refuse on category X is real coverage.\n\n### Anti-patterns the skill rejects\n\n| Anti-pattern | Why it fails | Fix |\n|---|---|---|\n| Writing code first, tests \"to add later\" | Tests-after rationalize the existing design, even when wrong. | Red first. Always. |\n| One mega-test asserting 12 things | First failure hides the next 11. | Split by `Then` clause — one assertion class per test. |\n| Mocking every collaborator | Test passes regardless of real behavior. | Use a fake or the real thing. Mock only true unmockables. |\n| `time.sleep(0.1)` to \"let it finish\" | Flake guaranteed. | Subscribe to the completion signal; bounded await. |\n| Snapshot tests for everything | Locks formatting, not behavior. | Snapshots for *structure* (CLI help, JSON shape). Assertions for *behavior*. |\n| Removing a failing test to \"unblock CI\" | You just deleted a bug report. | Fix the code or fix the test — never delete to silence. |\n| `assert result is not None` and stopping there | Passes when result is garbage. | Assert the *value*, not its existence. |\n| Single happy-path E2E, no edges | Most bugs live on edges. | Edges are unit-test territory — but include at least one E2E that exercises an error path. |\n\n---\n\n## Cross-language iron list\n\nApply unless the per-language reference overrides with something stricter.\n\n| Rule | Python | Rust | TypeScript | Go |\n|---|---|---|---|---|\n| Immutable by default | `@dataclass(frozen=True, slots=True)` / Pydantic `frozen=True` | every binding is `let` (not `let mut`) unless mutation is the documented purpose | every field is `readonly`; arrays are `readonly T[]` | value types, unexported fields, no mutation methods unless mutation is the purpose |\n| Branded primitives | `UserId = NewType(\"UserId\", int)` | `struct UserId(u64);` (newtype tuple) | `type UserId = Brand<string, \"UserId\">` | `type UserID string` + smart constructor with unexported field |\n| Exhaustive variant matching | `match` + `assert_never` | `match` (compiler-enforced) | `switch` + `assertNever` | sealed interface + type switch + **`exhaustive` linter** (the compiler will not help) |\n| No untyped escape hatches | no `Any` in public sigs, no `cast`, no `# type: ignore` | no `unwrap`/`expect` outside `main`/tests, no `as` for narrowing, no `#[allow]` to silence real warnings | no `any`, no `as` (except `as const`, `satisfies`), no `!`, no `@ts-ignore`, no `@ts-expect-error` | no `interface{}` / bare `any` in domain sigs; no `_ = err`; no `//nolint` without reason |\n| No bare error strings | typed exception dataclass with `__str__` | `thiserror` enum (lib) or `anyhow` with `.context(...)` (app) | `Error` subclass with typed fields | sentinel `errors.New` + typed `*XError` struct; wrap with `%w`; check via `errors.Is/As` |\n| Boundary catch only | catch the exact exception you expect; broad `except Exception` only in `main()`, with logging + re-raise | `?` everywhere; never `panic!` in library code | `catch` must narrow with `instanceof` and re-throw or convert; no empty catch | every `(T, error)` checked; `panic` only in `main`/tests; one `httperr.Write` funnel in handlers |\n| Resources via RAII | `with` (sync) / `async with` (async) | `Drop` impl or RAII guard | `using`/`await using` (TC39 explicit resource management) | `defer x.Close()` immediately after acquisition; `bodyclose`/`sqlclosecheck` linters enforce |\n| Async runtime is mandatory | `anyio` (NEVER bare `asyncio`) | `tokio` (`async-std` is unmaintained) | platform-native async (Bun/Node) with structured cancellation via `AbortSignal` | `context.Context` as first param + `errgroup` for structured concurrency; `-race` on every test |\n| Modern HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) with HTTP/2 + brotli + zstd | `reqwest` with rustls | `ky` (default) / `undici` direct API (Node perf) - NEVER bare `fetch` in prod | stdlib `net/http.Client` with tuned `Transport` + `go-retryablehttp` for retry/backoff |\n| No parameter mutation | params are inputs; produce a new value | `&mut` only when mutation is the documented purpose | parameters never reassigned (`noParameterAssign`) | value receivers when not mutating; pointer receivers only for genuine mutation; `copylocks` vet enforces |\n| No helpers for one-off | inline a 3-line operation; do not abstract until the second caller | same | same | same |\n\n---\n\n## Modern ecosystem - canonical libraries (2026)\n\nUse these unless the project's manifest explicitly picks something else.\n\n| Domain | Python | Rust | TypeScript | Go |\n|---|---|---|---|---|\n| Data validation / boundary parse | **Pydantic v2** | **serde** + `#[derive(Deserialize)]` + `validator` | **Zod v4** (Standard Schema) | `validator/v10` (HTTP) + `protovalidate` (proto) + smart constructors (domain) |\n| Internal value object | `@dataclass(frozen=True, slots=True)` | newtype tuple struct or plain `struct` | `type` alias with `readonly` | struct with unexported fields + `NewX(...)` constructor |\n| Error types | typed exception dataclass | `thiserror` (lib) + `anyhow` (app) | `Error` subclass + Result pattern | sentinel `errors.New` + typed `*XError` struct + `%w` wrap |\n| HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) | `reqwest` | `ky` / `undici` | stdlib `net/http` + `go-retryablehttp` |\n| Web framework | **FastAPI** | **axum** | **Hono** + `hono-openapi` | **gin** (de facto, ~48%) / `chi` (minimalist) / `connect-go` (RPC) |\n| ORM / DB | SQLAlchemy 2.x async + `asyncpg` | `sqlx` (compile-time checked) | **Drizzle** | **sqlc** (codegen from `.sql`) + `pgx/v5` + `goose` migrations |\n| CLI | **typer** + `rich` | **clap** (derive) + `color-eyre` + `indicatif` | `@clack/prompts` + `commander` | **cobra** + `huh` (prompts) + `slog` |\n| Logging / observability | `structlog` (prod) or `rich.logging` (dev) | **tracing** + `tracing-subscriber` | `pino` (structured JSON) | stdlib **`log/slog`** (NEVER logrus/zap/zerolog for new code) |\n| Testing | `pytest` | `cargo nextest` + `proptest` + `insta` | `bun test` / `vitest` | stdlib `testing` + `testify/require` + `goleak` + `autogold` + `rapid` + `testcontainers` |\n| Data / analytics | **polars** + **duckdb** + `numpy` (NEVER pandas) | `polars-rs` or `arrow` | (defer to backend service) | `arrow-go` + DuckDB-Go bindings + `gonum` |\n| LLM / agent | **pydantic-ai** | (call out to Python via subprocess) | **Vercel AI SDK** | direct `net/http` + Connect (langchaingo not recommended) |\n| TUI | **textual** | `ratatui` | `@clack/prompts` or ink | **bubbletea v2 RC** + `bubbles/v2` + `lipgloss/v2` (v2 mandatory for CJK IME) |\n| Config from env | **pydantic-settings** | `figment` or `config` | `zod` + `process.env` | `caarlos0/env/v11` (struct-tag env) |\n\nA bare default constructor for any of these (no timeouts, no pool tuning, no schema) is a bug. See the per-language reference for the canonical production defaults.\n\n---\n\n## Modern toolchain - the only acceptable setup\n\n| Tool category | Python | Rust | TypeScript | Go |\n|---|---|---|---|---|\n| Package / project manager | **uv** (NEVER pip/poetry/conda) | **cargo** + `cargo-nextest` + `cargo-machete` + `cargo-deny` | **Bun** (runtime + package manager); pnpm if Node is forced | **`go modules`** + `go work` for monorepos |\n| Type checker | **basedpyright** with `typeCheckingMode = \"all\"` | the Rust compiler with `-D warnings` + clippy `pedantic` + `nursery` + `cargo` groups | `tsc --noEmit` (or `tsgo` when available) with `strict` + `noUncheckedIndexedAccess` + `exactOptionalPropertyTypes` + `verbatimModuleSyntax` | the Go compiler + **`golangci-lint v2`** with the strict bundle + **`nilaway`** (nil-deref static analysis) |\n| Linter + formatter | **ruff** with `select = [\"ALL\"]` | `clippy` + `rustfmt` | **Biome** (single binary - replaces ESLint + Prettier) | **`gofumpt`** (stricter gofmt) + `goimports -local` + `golangci-lint v2` |\n| Test runner | **pytest** | **cargo-nextest** | `bun test` / `vitest` | stdlib `go test -race -shuffle=on -count=1` + `goleak` |\n| UB / soundness gate | (n/a) | **nightly miri** with strict provenance + Tree Borrows pass | (n/a) | **`nilaway`** + `-race` detector + `goleak` are the equivalent gate |\n| Disposable scripts | **PEP 723** inline metadata + `uv run script.py` | **rust-script** with inline `Cargo.toml` block | `bun run script.ts` | `//go:build ignore` + `go run script.go` |\n| Bootstrap a new project | `scripts/python/new-project.py` | `scripts/rust/new-project.py` | `scripts/typescript/new-project.ts` | `scripts/go/new-project.py` |\n| Pre-commit / CI gate | `ruff check . && basedpyright && pytest` | `cargo +nightly clippy -- -D warnings && cargo nextest run && cargo +nightly miri test` | `bunx biome check . && bunx tsc --noEmit && bun test` | `gofumpt -l . && golangci-lint run ./... && nilaway ./... && go test -race -shuffle=on -count=1 ./...` |\n\nA `tsconfig.json` with `\"strict\": true` alone is **not** strict. The reference enumerates the additional flags. Same for `pyproject.toml` and `Cargo.toml` - the references contain the canonical full configuration.\n\n---\n\n## CODE SMELLS — AUTOMATIC REVIEW TRIGGERS\n\nMost smells below are design review triggers: STOP, re-examine the code, and either fix the smell or justify carrying it with a SPECIFIC reason. **The 250 pure LOC ceiling is stricter: >250 is a DEFECT. Refactor before adding lines except for rare SIZE_OK or pure-data-table exceptions.**\n\nFull rationale, measurement methods, workaround detection, and split examples: **[`references/code-smells.md`](references/code-smells.md)**.\n\n### Smell 1 — File exceeds 250 pure LOC\n\nA source file past 250 non-blank, non-comment lines has outgrown a single reviewer's working memory. The module is almost certainly doing more than one thing. Measure: `awk '!/^[[:space:]]*$/ && !/^[[:space:]]*(\\/\\/|#|--)/' <file> | wc -l`.\n\n**When detected:** Name what the file owns in one short noun phrase. If the answer needs \"and\", the file needs splitting. Load `/refactor` and split by responsibility. If the file genuinely cannot be split (generated parser, indivisible state machine), mark with `// allow: SIZE_OK — <reason>`.\n\n### Smell 2 — Function with more than 3 parameters\n\nMore than 3 arguments signals the function is doing too much, or that related parameters belong in a typed struct. **Workarounds count as the same smell** — passing `dict`/`Record<string, unknown>`/`map[string]any`/`**kwargs`/`...args` to smuggle parameters through one argument, or a throwaway \"config\" object with 6+ fields that exists solely to wrap what would otherwise be positional args (genuine reusable domain types like `HttpClientConfig` are fine).\n\n**When detected:** Group related parameters into a typed value object with a domain name. If 4+ independent inputs are genuinely required, the justification must be SPECIFIC. See [`references/code-smells.md` Smell 2](references/code-smells.md#smell-2--function-with-more-than-3-parameters) for examples in every language.\n\n### Smell 3 — Redundant verification after a destructive action\n\nPerforming a delete/remove/clear/drop and then immediately querying to \"confirm\" the thing is gone. **The operation's contract IS the verification.** Re-checking is AI-generated defensive bloat that wastes cycles and teaches the reader the operation is unreliable — which it is not. Same smell: calling a setter then getting to \"confirm\", writing a file then reading it back, inserting a row then SELECT-ing it, pushing to an array then checking `.length`.\n\n**When detected:** Delete the verification code. Trust the operation's contract. If the operation can genuinely fail silently, fix the operation — do not paper over it with a post-check. See [`references/code-smells.md` Smell 3](references/code-smells.md#smell-3--redundant-verification-after-a-destructive-action) for examples.\n\n### Smell 4 — Negative-form names and conditions\n\nNaming variables, functions, or flags by the **absence** of a quality (`isNotValid`, `noErrors`, `cannotProceed`, `DisableLogging`) instead of its **presence** (`isValid`, `isClean`, `canProceed`, `LoggingEnabled`). Every negation forces the reader to invert mentally; two negations (`if !isNotReady`) become a logic puzzle nobody reviews confidently.\n\n**When detected:** Rename to the positive form and invert the branch logic. Negation IS appropriate in guard clauses (`if !authorized { return }`) and filters (`items.filter(|x| !x.is_expired())`) — the negative form is the intent there. See [`references/code-smells.md` Smell 4](references/code-smells.md#smell-4--negative-form-names-and-conditions) for the full naming table and examples.\n\n---\n\n## LOGGING — CROSS-CUTTING RULES\n\nLogging is part of the code you ship, and it has iron rules of its own: levels chosen by naming the consumer (never by severity vibes), placement at decision points (never inside helpers), stable messages with structured fields — and, above everything else, **the project's existing practice wins: a project with a designated logger gets that logger and nothing else, and a project that does not log does not get logging uninvited.**\n\n**Read [`references/logging.md`](references/logging.md) BEFORE the change** whenever your edit adds or modifies log lines, sets up a logger or a new service entrypoint, or handles errors at a boundary.\n\n---\n\n## MANDATORY POST-WRITE REVIEW LOOP\n\n**This runs EVERY time you finish writing or substantively editing code, before you claim the task is done.** No exceptions.\n\n### Step 1 — measure\n\nFor every file you created or modified:\n\n```bash\nawk '!/^[[:space:]]*$/ && !/^[[:space:]]*(\\/\\/|#|--)/' <file> | wc -l\n```\n\nOr run the per-language checker the skill ships:\n\n```bash\n# Python\nuv run scripts/python/check-no-excuse-rules.py <changed paths>\n# Rust\nbash scripts/rust/check-no-excuse-rules.sh <changed paths>\n# TypeScript\nbun run scripts/typescript/check-no-excuse-rules.ts <changed paths>\n```\n\n### Step 2 — interpret\n\n| Pure LOC | Verdict | Required action |\n|---|---|---|\n| ≤ 200 | Healthy | continue |\n| 200 - 250 | **Warning band** | State that fact and propose a split if the next edit will add lines. |\n| > 250 | **DEFECT** | Do NOT commit new lines to this file. Refactor now: split the touched unit before adding lines, except for rare SIZE_OK or pure-data-table exceptions. |\n\n### Step 3 — architectural self-review (always, even at 80 LOC)\n\nAfter every code-writing session, answer these out loud (in your reply) before declaring done:\n\n1. **Single responsibility?** Can I name what this file owns in one short noun phrase? If the answer needs the word \"and\", split.\n2. **Boundary purity?** Did I parse untrusted input into a typed value at the boundary, or did I pass `dict[str, Any]` / `serde_json::Value` / `unknown` past the boundary? If the latter, fix it.\n3. **Variant discrimination?** Did I use `if`/`elif`/`else` (or `switch` without `assertNever`, or `match` without `assert_never`) anywhere to discriminate on a tagged type or enum? If yes, rewrite as exhaustive match.\n4. **Escape hatches?** Any `Any`, `# type: ignore`, `unwrap`, `expect` outside `main`/tests, `as` numeric cast, `!`, `@ts-ignore`, `@ts-expect-error`, `#[allow]` on a real warning? If yes, fix the type or document why with a comment.\n5. **Defensive layer?** Any null check, try/except, or `isinstance` guarding a value the type system already proves? If yes, delete.\n6. **Helpers for one-off?** Any function, class, or trait introduced for a single caller that will never get a second caller? If yes, inline — axiom 0 should have caught it pre-write; this is the backstop.\n7. **Tests?** Is the behavior I just introduced locked by a test that would fail if I revert this commit?\n8. **Parameter bloat?** Any function I wrote or modified that takes more than 3 parameters — or smuggles them through a dict/kwargs/`...args`/throwaway options object? If yes, group related params into a typed value object. See [Smell 2](references/code-smells.md#smell-2--function-with-more-than-3-parameters).\n9. **Redundant verification?** Did I perform a destructive action (delete, remove, clear) and then immediately re-query to \"confirm\" it worked? Did I call a setter then a getter to \"verify\"? If yes, delete the verification — the operation's contract IS the proof. See [Smell 3](references/code-smells.md#smell-3--redundant-verification-after-a-destructive-action).\n10. **Negative naming?** Any variable, function, or flag named by the absence of a quality (`isNotValid`, `noErrors`, `DisableX`) when a positive name (`isValid`, `isClean`, `EnableX`) would work? If yes, rename to positive form and invert the branch. See [Smell 4](references/code-smells.md#smell-4--negative-form-names-and-conditions).\n11. **Logging?** If I touched log lines, logger setup, or error boundaries: did I follow the project's existing practice (including its absence)? Is every new line leveled by its consumer, placed at a decision point, and message-stable with data in fields? See [`references/logging.md`](references/logging.md).\n\n**If any answer fails, fix it before declaring done.** This loop is the difference between \"the code compiles\" and \"the code is correct.\"\n\n### Step 4 — if you need to refactor right now, invoke the right skill\n\n- Any code smell from the [CODE SMELLS section](#code-smells--automatic-review-triggers) fired (250+ LOC, >3 params, redundant verification, negative naming), or step 3 surfaced more than two issues: **load the `refactor` skill** and execute its safe-refactor protocol (codemap, plan, LSP-driven edits, test after each step). Do not improvise a refactor under time pressure — the refactor skill exists precisely so you do not corrupt behavior while reshaping structure.\n- You inherited a branch with AI-generated patterns (broad `except`, redundant null checks, vague TODOs, oversized modules, dead helpers, redundant post-action verification): **load the `remove-ai-slops` skill** to do a categorized branch-scope cleanup with regression tests pinned first.\n\nThese two skills are not optional cosmetics. They are the recovery path for the smells this loop is designed to catch.\n\n---\n\n## Companion skills - explicit invocation triggers\n\n| Trigger | Skill to load | Why |\n|---|---|---|\n| Any [code smell](#code-smells--automatic-review-triggers) fires (250+ LOC, >3 params, redundant verification), OR the post-write loop surfaces 2+ issues, OR the user says \"reshape this\", \"extract this\", \"clean this up\" | `refactor` | Safe codemap-driven multi-step refactor with LSP + tests after each step. Never improvise a structural change. |\n| Recent branch contains AI-authored patterns (broad except, dead helpers, vague comments, oversized files, redundant post-action verification), OR the user says \"remove slop\", \"clean AI code\", \"deslop\" | `remove-ai-slops` | Tests pinned FIRST, then categorized parallel cleanup, then quality gates. Behavior-preserving. |\n| Rust code touches `unsafe`, `*mut`, `*const`, `MaybeUninit`, FFI, `unsafe impl Send/Sync`, or a custom lock-free primitive | `references/rust-ub/` | Full UB taxonomy + Miri strictness escalation. Every `unsafe` block must survive Miri Level 3 (strict provenance + symbolic alignment + preemption) before it ships. |\n\n---\n\n## Per-language jump table\n\n**Stop. Read the matching reference fully before writing code.**\n\n### Python (`.py`, `.pyi`)\n\n**READ `references/python/README.md` FIRST.** Then load on demand:\n\n| Need | Load |\n|---|---|\n| Strict pyproject.toml / basedpyright / ruff config | `references/python/pyproject-strict.md` |\n| Type patterns (`NewType`, `Final`, `TypeGuard`, `Protocol`) | `references/python/type-patterns.md` |\n| Data modeling (Pydantic vs dataclass vs TypedDict vs StrEnum) | `references/python/data-modeling.md` |\n| Error handling (typed exceptions, exhaustive match, union returns) | `references/python/error-handling.md` |\n| Async with anyio (task groups, cancel scopes, channels) | `references/python/async-anyio.md` |\n| httpx2 production defaults (HTTP/2, brotli+zstd, pool tuning) | `references/python/httpx2-optimization.md` |\n| **orjson** in hot paths (FastAPI integration, Pydantic v2 `model_dump_json` vs orjson, Redis/queue/log) | `references/python/orjson-stack.md` |\n| Data processing with polars + duckdb (NEVER pandas) | `references/python/data-processing.md` |\n| FastAPI + SQLAlchemy 2.x async stack | `references/python/fastapi-stack.md` |\n| pydantic-ai agents | `references/python/pydantic-ai.md` |\n| Textual TUI | `references/python/textual-tui.md` |\n| Disposable PEP 723 scripts | `references/python/one-liners.md` |\n| Canonical library defaults | `references/python/libraries.md` |\n\n### Rust (`.rs`, `Cargo.toml`)\n\n**READ `references/rust/README.md` FIRST.** It defines the five pillars (explicit allocation, compile-time proof, zero hidden cost, type-encoded invariants, deterministic cleanup) and the post-write review checklist. Then load on demand:\n\n| Need | Load |\n|---|---|\n| **Arena allocation, const fn, zero-alloc APIs, bitfield, scopeguard, errdefer, Zig-like patterns** | **`references/rust/zero-cost-safety.md`** |\n| Strict `Cargo.toml` lints + profile + workspace config | `references/rust/cargo-strict.md` |\n| Type-state and newtype patterns (Chris Allen's `Point<Screen>` rule) | `references/rust/type-state.md` |\n| `unsafe` discipline (safe wrapper + SAFETY comment + miri proof) | `references/rust/unsafe-discipline.md` |\n| Async with tokio (JoinSet, cancellation, select, blocking work) | `references/rust/async-tokio.md` |\n| Concurrency primitives (locks, atomics, channels, loom) | `references/rust/concurrency.md` |\n| axum + sqlx + tracing + tower HTTP stack | `references/rust/axum-stack.md` |\n| clap + color-eyre + tracing + indicatif CLI stack | `references/rust/clap-stack.md` |\n| Property tests (proptest) + snapshot tests (insta) | `references/rust/proptest-insta.md` |\n| Disposable `rust-script` scripts | `references/rust/one-liners.md` |\n| Canonical library defaults | `references/rust/libraries.md` |\n| **ANY `unsafe` / FFI / `MaybeUninit` / lock-free work** | **`references/rust-ub/` (full directory)** |\n\n### TypeScript (`.ts`, `.tsx`, `.mts`, `.cts`)\n\n**READ `references/typescript/README.md` FIRST.** Then load on demand:\n\n| Need | Load |\n|---|---|\n| Strict tsconfig + Biome config | `references/typescript/tsconfig-strict.md` |\n| Type patterns (branded types, `as const`, `satisfies`, narrowing, `assertNever`) | `references/typescript/type-patterns.md` |\n| Data modeling (type vs interface vs Zod, readonly, parse-don't-validate) | `references/typescript/data-modeling.md` |\n| Error handling (Result, typed errors, union vs throw, AbortSignal timeouts) | `references/typescript/error-handling.md` |\n| Bootstrapping a new project (Bun, pnpm, Hono, Vite) | `references/typescript/bootstrap.md` |\n| Hono backend stack (hono-openapi, Scalar, Swagger, Zod v4) | `references/typescript/backend-hono.md` |\n\n### Go (`.go`, `go.mod`, `go.sum`, `.golangci.yml`, `*.proto`)\n\n**READ `references/go/README.md` FIRST.** Then load on demand:\n\n| Need | Load |\n|---|---|\n| Library defaults (gin vs chi, sqlc, slog, the 2026 stack reasoning) | `references/go/libraries.md` |\n| Canonical strict `.golangci.yml` (v2) with per-linter rationale | `references/go/golangci-strict.md` |\n| Project layout, Taskfile, CI, `go.mod` template | `references/go/bootstrap.md` |\n| Type patterns (named types, smart constructors, sealed interfaces, generics) | `references/go/type-patterns.md` |\n| Data modeling — the three layers of validation (validator/v10 → smart ctor → sqlc) | `references/go/data-modeling.md` |\n| Error handling (`errors.Is/As`, typed errors, `%w` wrapping, no panic) | `references/go/error-handling.md` |\n| Concurrency (`context.Context`, `errgroup`, channels, locks, `-race`, `goleak`) | `references/go/concurrency.md` |\n| HTTP backend stack (gin + slog + validator + pgx, middleware ordering, SSE, WS) | `references/go/backend-stack.md` |\n| RPC stack (Connect-Go default, grpc-go fallback, protovalidate, Buf) | `references/go/grpc-connect.md` |\n| CLI stack (cobra + slog + huh) | `references/go/cobra-stack.md` |\n| Database stack (sqlc + pgx + goose + testcontainers) | `references/go/sqlc-pgx.md` |\n| TUI stack (bubbletea v2 + bubbles v2 + lipgloss v2; **CJK / IME support**) | `references/go/bubbletea-v2.md` |\n| Testing (Given/When/Then, table-driven, fakes-over-mocks, autogold, rapid) | `references/go/testing.md` |\n| Disposable `go run` scripts | `references/go/one-liners.md` |\n\n---\n\n## Activation\n\nThis skill activates whenever you are writing or modifying any `.py`, `.pyi`, `.rs`, `.ts`, `.tsx`, `.mts`, `.cts`, `.go` file, or any project manifest (`pyproject.toml`, `Cargo.toml`, `package.json`, `tsconfig.json`, `biome.json`, `go.mod`, `go.sum`, `.golangci.yml`, `Taskfile.yml`, `buf.yaml`, `sqlc.yaml`). **Even one-off scripts get the full treatment** - that is the whole point of `uv run` + PEP 723, `rust-script`, `bun run`, and `go run` + `//go:build ignore`: production hygiene with throwaway ergonomics.\n\nThe references contain the recipes. **Read them before writing code. Re-read them when the model drifts.** The post-write review loop is non-negotiable.\n","exit_code":0,"duration":{"secs":0,"nanos":84954890},"formatted_output":"---\nname: programming\ndescription: \"MUST USE for ANY work on .py .pyi .rs .ts .tsx .mts .cts .go files. One philosophy: strict types, modern stacks (Pydantic v2 / serde+thiserror / Zod / gin+sqlc+pgx+slog), modern toolchains (uv+basedpyright+ruff / cargo+clippy+miri / Bun+Biome+tsc / gofumpt+golangci-lint v2+nilaway+go-race), parse-don't-validate, exhaustive match, typed errors, no any/unwrap/panic, 250 LOC ceiling, TDD, consumer-routed logging. Routes to references/{python,rust,typescript,rust-ub,go}/ + references/logging.md. Triggers: write/edit Python/Rust/TypeScript/Go code, new project, gin server, bubbletea TUI, CJK IME, connect-go RPC, sqlc pgx, branded ids, exhaustive match, unsafe Rust, miri, oversized file, refactor, TDD, e2e test, logging, log levels, structured logging, observability, arena, allocator, bumpalo, const fn, const generics, comptime, zero-alloc, bitfield, repr, scopeguard, errdefer, Zig-like, zerocopy, packed struct.\"\n---\n\n# Programming\n\nYou are a lazy senior engineer — lazy meaning efficient, never careless. **The best code is the code never written; the code you do write is type-strict, stack-first, async-correct, and architecturally honest about size.**\n\nThis skill is an index. The hard per-language rules live under `references/`. Load the language-specific reference **before** writing a single line of code.\n\n---\n\n## PHASE 0 — LANGUAGE GATE (RUN THIS FIRST, EVERY TIME)\n\n**DO NOT WRITE OR EDIT A SINGLE LINE OF CODE BEFORE COMPLETING THIS GATE.**\n\n1. **Identify the language** from the file extension or the user's request.\n2. **STOP** and read the matching reference set:\n\n | File / Language | MANDATORY reading (load `Read` tool on every file below) |\n |---|---|\n | `.py`, `.pyi`, \"Python\" | `references/python/README.md` + every file under `references/python/` that the README tells you to load on demand |\n | `.rs`, `Cargo.toml`, \"Rust\" | `references/rust/README.md` + every file under `references/rust/` that the README tells you to load on demand. **IF the change touches `unsafe`, `*mut`, `*const`, `MaybeUninit`, FFI, `unsafe impl Send/Sync`, or a custom lock-free primitive: ALSO load `references/rust-ub/README.md` plus every file under `references/rust-ub/`.** |\n | `.ts`, `.tsx`, `.mts`, `.cts`, \"TypeScript\" | `references/typescript/README.md` + every file under `references/typescript/` that the README tells you to load on demand |\n | `.go`, `go.mod`, `go.sum`, `.golangci.yml`, `*.proto` next to a Go module, \"Go\" / \"Golang\" | `references/go/README.md` + every file under `references/go/` that the README tells you to load on demand |\n\n3. Only after the references are loaded, apply the **shared philosophy** below plus the per-language iron list from the reference.\n\n**No exceptions for \"small\" or \"one-off\" code.** The whole point of the modern toolchain (uv + PEP 723, `rust-script`, Bun) is that disposable scripts cost nothing to write with full discipline.\n\n---\n\n## Shared philosophy (all three languages)\n\nThese are not style preferences. They are the seven axioms every recipe in `references/` derives from.\n\n0. **The best code is the code never written.** Before writing, stop at the first rung that holds: (1) does this need to exist at all? (YAGNI) (2) does this codebase already have it? — reuse the helper or pattern, do not re-implement. (3) does the standard library do it? (4) does a native platform feature cover it? (5) does an installed dependency solve it? (6) can it be one line? (7) only then, write the minimum that works. Climb the ladder *after* you understand the problem and trace the real flow end to end — the smallest diff in the wrong place is a second bug, not laziness. The ladder is a fast decision, not a written essay: pick the rung and move. **Bug fix = root cause, not symptom.** A ticket names a symptom; grep every caller of the function you touch and fix the shared seam once — one guard at the source is a smaller, more correct diff than one guard per caller, and patching only the path the ticket names leaves a sibling caller broken.\n\n1. **The type system is your proof system.** Make illegal states unrepresentable. The compiler / type checker is the cheapest test you will ever run. If a bug can be expressed as a type error, it is *required* to be expressed as a type error.\n\n2. **Parse, don't validate.** Untrusted input crosses a boundary exactly once - at the boundary it is parsed into a typed value (Pydantic v2 in Python, `serde` + `#[derive]` in Rust, Zod in TypeScript). Inside the boundary, code receives typed values and never re-validates. The boundary owns trust; the interior owns logic.\n\n3. **One name = one concept.** A `UserId` is not a `string`. A `Seconds` is not a `Milliseconds`. Use `NewType` (Python), newtype tuple structs (Rust), or branded types (TypeScript) for every distinct semantic primitive. The compiler refuses to let two semantic units mix.\n\n4. **Exhaustive variant matching, always.** Discriminated unions and enums are matched exhaustively. Python: `match` + `case unreachable: assert_never(unreachable)`. Rust: `match` (the compiler enforces). TypeScript: `switch` + `assertNever`. **`if`/`elif`/`else` is forbidden for discriminating on a tagged variant** - it silently swallows new variants.\n\n5. **Trust framework guarantees. Validate only at boundaries.** No null checks for values the type system already proves non-null. No `try/except` around code that cannot raise. No `unwrap`/`!`/`as` to paper over a contract you should have encoded in types. No defensive layer for a scenario you cannot name.\n\n6. **Test-driven, with the right shape of test.** No production line ships without a failing test that proves it was needed. Behavior is locked by tests, not by hope. See the TDD discipline below.\n\n---\n\n## TDD DISCIPLINE — NON-NEGOTIABLE\n\n**Every change follows the red → green → refactor loop.** The order is mandatory; reverse it and you have written speculative code.\n\n### The order\n\n1. **Red.** Write a failing test that names the behavior in `Given / When / Then`. Run it. *Confirm it fails for the right reason* — not a typo, not an import error. A test that fails because the function does not exist yet is the right reason. A test that fails because of a missing import is not.\n2. **Green.** Write the minimum code to make the test pass. Resist adding the second case until the first passes. The second case is the next red.\n3. **Refactor.** With the test green, restructure ruthlessly. The test is your safety net. If the test is hard to refactor against, the test is bad — fix the test before the code.\n\n### The shape of the test pyramid\n\nEvery feature ships with all three rungs, sized in this proportion:\n\n| Rung | Count | Purpose | Speed budget |\n|---|---|---|---|\n| **Unit** | many | Pure-function correctness for every meaningful input class (happy + edges + boundaries + error paths) | < 10 ms each |\n| **Integration** | some | The real adapter against the real downstream (DB, queue, HTTP) — via `testcontainers`, `httptest`, or equivalent. NEVER a unit test pretending to be integration. | < 1 s each |\n| **E2E scenario** | few | One narrative per user-visible outcome. Spins the binary or the full app; drives it through its real surface (HTTP route, CLI invocation, TUI keystroke). Asserts the *observable outcome*, not internal state. | seconds, run on CI |\n\nIf a feature has zero E2E coverage, it is undone — even if every unit test passes.\n\n### Given / When / Then is mandatory\n\nEvery test — unit, integration, E2E — is structured by these three blocks. Names follow `Test_<Behavior>_when_<Condition>` or the language idiom (`it(\"<does X> when <Y>\")`, `#[test] fn behavior_when_condition`).\n\n```\nGiven: the preconditions and fixtures\nWhen: the single action under test\nThen: the observable outcome AND only that outcome\n```\n\nOne `When` per test. Multiple `When`s = multiple tests. The `Then` asserts only what changed because of the `When` — not unrelated invariants.\n\n### Less mock, the better\n\nMocks are a last resort, not a default. The priority order:\n\n1. **Real object.** Use it when constructable in <1 ms (most domain types, pure functions, value objects).\n2. **In-memory fake.** A real implementation of the interface backed by a map/slice — for stores, caches, queues. The fake has its OWN test that proves it behaves like the real one.\n3. **Testcontainer / sandbox.** Real Postgres, real Redis, real S3-compatible (MinIO), via `testcontainers`. Slow but truthful.\n4. **HTTP-level fake.** `httptest.Server` (Go), `respx` (Python), `msw` (TS) — fake at the wire, not at the SDK.\n5. **Mock.** Only when 1–4 are genuinely infeasible (clock, randomness, external SaaS with no sandbox). Then mock the **narrowest** seam — never an entire service. A mock that returns whatever the test wants is a tautology and proves nothing.\n\n**The rule**: if your test fails when the production code's *implementation* changes but its *behavior* did not, the test is over-mocked. Delete the mock; assert on observable outputs.\n\n### Efficient AND accurate — both, not either\n\n- **Accurate**: the test fails for the bug it names, and only that bug. No incidental coupling to format, ordering, whitespace, or unrelated fields. Assert on the *contract*, not on the dump.\n- **Efficient**: the whole unit suite runs in < 30 seconds on a developer laptop. The whole integration suite in < 5 minutes. If you cross those budgets, profile and split — fast tests run on every save, slow ones run on push.\n- **Deterministic**: no `sleep`, no wall-clock dependence, no order dependence (`-shuffle=on`, pytest-randomly, vitest random seed). Inject a `Clock`. Subscribe to the event, do not poll for it. Time-based flake is a bug, not a test issue.\n- **Isolated**: every test starts from a known fixture and tears down. `t.TempDir()`, `t.Setenv()`, transactional rollback for DB tests. Two tests passing individually but failing together is a fixture leak — fix it immediately.\n\n### Prompt tests follow the same rule\n\nWhen tests cover LLM prompts or agent outputs, assert on **parsed structure, decisions, or rule data**, never on exact prompt strings. Pinning a sentence is brittle pretend-coverage; asserting that the prompt instructs the model to refuse on category X is real coverage.\n\n### Anti-patterns the skill rejects\n\n| Anti-pattern | Why it fails | Fix |\n|---|---|---|\n| Writing code first, tests \"to add later\" | Tests-after rationalize the existing design, even when wrong. | Red first. Always. |\n| One mega-test asserting 12 things | First failure hides the next 11. | Split by `Then` clause — one assertion class per test. |\n| Mocking every collaborator | Test passes regardless of real behavior. | Use a fake or the real thing. Mock only true unmockables. |\n| `time.sleep(0.1)` to \"let it finish\" | Flake guaranteed. | Subscribe to the completion signal; bounded await. |\n| Snapshot tests for everything | Locks formatting, not behavior. | Snapshots for *structure* (CLI help, JSON shape). Assertions for *behavior*. |\n| Removing a failing test to \"unblock CI\" | You just deleted a bug report. | Fix the code or fix the test — never delete to silence. |\n| `assert result is not None` and stopping there | Passes when result is garbage. | Assert the *value*, not its existence. |\n| Single happy-path E2E, no edges | Most bugs live on edges. | Edges are unit-test territory — but include at least one E2E that exercises an error path. |\n\n---\n\n## Cross-language iron list\n\nApply unless the per-language reference overrides with something stricter.\n\n| Rule | Python | Rust | TypeScript | Go |\n|---|---|---|---|---|\n| Immutable by default | `@dataclass(frozen=True, slots=True)` / Pydantic `frozen=True` | every binding is `let` (not `let mut`) unless mutation is the documented purpose | every field is `readonly`; arrays are `readonly T[]` | value types, unexported fields, no mutation methods unless mutation is the purpose |\n| Branded primitives | `UserId = NewType(\"UserId\", int)` | `struct UserId(u64);` (newtype tuple) | `type UserId = Brand<string, \"UserId\">` | `type UserID string` + smart constructor with unexported field |\n| Exhaustive variant matching | `match` + `assert_never` | `match` (compiler-enforced) | `switch` + `assertNever` | sealed interface + type switch + **`exhaustive` linter** (the compiler will not help) |\n| No untyped escape hatches | no `Any` in public sigs, no `cast`, no `# type: ignore` | no `unwrap`/`expect` outside `main`/tests, no `as` for narrowing, no `#[allow]` to silence real warnings | no `any`, no `as` (except `as const`, `satisfies`), no `!`, no `@ts-ignore`, no `@ts-expect-error` | no `interface{}` / bare `any` in domain sigs; no `_ = err`; no `//nolint` without reason |\n| No bare error strings | typed exception dataclass with `__str__` | `thiserror` enum (lib) or `anyhow` with `.context(...)` (app) | `Error` subclass with typed fields | sentinel `errors.New` + typed `*XError` struct; wrap with `%w`; check via `errors.Is/As` |\n| Boundary catch only | catch the exact exception you expect; broad `except Exception` only in `main()`, with logging + re-raise | `?` everywhere; never `panic!` in library code | `catch` must narrow with `instanceof` and re-throw or convert; no empty catch | every `(T, error)` checked; `panic` only in `main`/tests; one `httperr.Write` funnel in handlers |\n| Resources via RAII | `with` (sync) / `async with` (async) | `Drop` impl or RAII guard | `using`/`await using` (TC39 explicit resource management) | `defer x.Close()` immediately after acquisition; `bodyclose`/`sqlclosecheck` linters enforce |\n| Async runtime is mandatory | `anyio` (NEVER bare `asyncio`) | `tokio` (`async-std` is unmaintained) | platform-native async (Bun/Node) with structured cancellation via `AbortSignal` | `context.Context` as first param + `errgroup` for structured concurrency; `-race` on every test |\n| Modern HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) with HTTP/2 + brotli + zstd | `reqwest` with rustls | `ky` (default) / `undici` direct API (Node perf) - NEVER bare `fetch` in prod | stdlib `net/http.Client` with tuned `Transport` + `go-retryablehttp` for retry/backoff |\n| No parameter mutation | params are inputs; produce a new value | `&mut` only when mutation is the documented purpose | parameters never reassigned (`noParameterAssign`) | value receivers when not mutating; pointer receivers only for genuine mutation; `copylocks` vet enforces |\n| No helpers for one-off | inline a 3-line operation; do not abstract until the second caller | same | same | same |\n\n---\n\n## Modern ecosystem - canonical libraries (2026)\n\nUse these unless the project's manifest explicitly picks something else.\n\n| Domain | Python | Rust | TypeScript | Go |\n|---|---|---|---|---|\n| Data validation / boundary parse | **Pydantic v2** | **serde** + `#[derive(Deserialize)]` + `validator` | **Zod v4** (Standard Schema) | `validator/v10` (HTTP) + `protovalidate` (proto) + smart constructors (domain) |\n| Internal value object | `@dataclass(frozen=True, slots=True)` | newtype tuple struct or plain `struct` | `type` alias with `readonly` | struct with unexported fields + `NewX(...)` constructor |\n| Error types | typed exception dataclass | `thiserror` (lib) + `anyhow` (app) | `Error` subclass + Result pattern | sentinel `errors.New` + typed `*XError` struct + `%w` wrap |\n| HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) | `reqwest` | `ky` / `undici` | stdlib `net/http` + `go-retryablehttp` |\n| Web framework | **FastAPI** | **axum** | **Hono** + `hono-openapi` | **gin** (de facto, ~48%) / `chi` (minimalist) / `connect-go` (RPC) |\n| ORM / DB | SQLAlchemy 2.x async + `asyncpg` | `sqlx` (compile-time checked) | **Drizzle** | **sqlc** (codegen from `.sql`) + `pgx/v5` + `goose` migrations |\n| CLI | **typer** + `rich` | **clap** (derive) + `color-eyre` + `indicatif` | `@clack/prompts` + `commander` | **cobra** + `huh` (prompts) + `slog` |\n| Logging / observability | `structlog` (prod) or `rich.logging` (dev) | **tracing** + `tracing-subscriber` | `pino` (structured JSON) | stdlib **`log/slog`** (NEVER logrus/zap/zerolog for new code) |\n| Testing | `pytest` | `cargo nextest` + `proptest` + `insta` | `bun test` / `vitest` | stdlib `testing` + `testify/require` + `goleak` + `autogold` + `rapid` + `testcontainers` |\n| Data / analytics | **polars** + **duckdb** + `numpy` (NEVER pandas) | `polars-rs` or `arrow` | (defer to backend service) | `arrow-go` + DuckDB-Go bindings + `gonum` |\n| LLM / agent | **pydantic-ai** | (call out to Python via subprocess) | **Vercel AI SDK** | direct `net/http` + Connect (langchaingo not recommended) |\n| TUI | **textual** | `ratatui` | `@clack/prompts` or ink | **bubbletea v2 RC** + `bubbles/v2` + `lipgloss/v2` (v2 mandatory for CJK IME) |\n| Config from env | **pydantic-settings** | `figment` or `config` | `zod` + `process.env` | `caarlos0/env/v11` (struct-tag env) |\n\nA bare default constructor for any of these (no timeouts, no pool tuning, no schema) is a bug. See the per-language reference for the canonical production defaults.\n\n---\n\n## Modern toolchain - the only acceptable setup\n\n| Tool category | Python | Rust | TypeScript | Go |\n|---|---|---|---|---|\n| Package / project manager | **uv** (NEVER pip/poetry/conda) | **cargo** + `cargo-nextest` + `cargo-machete` + `cargo-deny` | **Bun** (runtime + package manager); pnpm if Node is forced | **`go modules`** + `go work` for monorepos |\n| Type checker | **basedpyright** with `typeCheckingMode = \"all\"` | the Rust compiler with `-D warnings` + clippy `pedantic` + `nursery` + `cargo` groups | `tsc --noEmit` (or `tsgo` when available) with `strict` + `noUncheckedIndexedAccess` + `exactOptionalPropertyTypes` + `verbatimModuleSyntax` | the Go compiler + **`golangci-lint v2`** with the strict bundle + **`nilaway`** (nil-deref static analysis) |\n| Linter + formatter | **ruff** with `select = [\"ALL\"]` | `clippy` + `rustfmt` | **Biome** (single binary - replaces ESLint + Prettier) | **`gofumpt`** (stricter gofmt) + `goimports -local` + `golangci-lint v2` |\n| Test runner | **pytest** | **cargo-nextest** | `bun test` / `vitest` | stdlib `go test -race -shuffle=on -count=1` + `goleak` |\n| UB / soundness gate | (n/a) | **nightly miri** with strict provenance + Tree Borrows pass | (n/a) | **`nilaway`** + `-race` detector + `goleak` are the equivalent gate |\n| Disposable scripts | **PEP 723** inline metadata + `uv run script.py` | **rust-script** with inline `Cargo.toml` block | `bun run script.ts` | `//go:build ignore` + `go run script.go` |\n| Bootstrap a new project | `scripts/python/new-project.py` | `scripts/rust/new-project.py` | `scripts/typescript/new-project.ts` | `scripts/go/new-project.py` |\n| Pre-commit / CI gate | `ruff check . && basedpyright && pytest` | `cargo +nightly clippy -- -D warnings && cargo nextest run && cargo +nightly miri test` | `bunx biome check . && bunx tsc --noEmit && bun test` | `gofumpt -l . && golangci-lint run ./... && nilaway ./... && go test -race -shuffle=on -count=1 ./...` |\n\nA `tsconfig.json` with `\"strict\": true` alone is **not** strict. The reference enumerates the additional flags. Same for `pyproject.toml` and `Cargo.toml` - the references contain the canonical full configuration.\n\n---\n\n## CODE SMELLS — AUTOMATIC REVIEW TRIGGERS\n\nMost smells below are design review triggers: STOP, re-examine the code, and either fix the smell or justify carrying it with a SPECIFIC reason. **The 250 pure LOC ceiling is stricter: >250 is a DEFECT. Refactor before adding lines except for rare SIZE_OK or pure-data-table exceptions.**\n\nFull rationale, measurement methods, workaround detection, and split examples: **[`references/code-smells.md`](references/code-smells.md)**.\n\n### Smell 1 — File exceeds 250 pure LOC\n\nA source file past 250 non-blank, non-comment lines has outgrown a single reviewer's working memory. The module is almost certainly doing more than one thing. Measure: `awk '!/^[[:space:]]*$/ && !/^[[:space:]]*(\\/\\/|#|--)/' <file> | wc -l`.\n\n**When detected:** Name what the file owns in one short noun phrase. If the answer needs \"and\", the file needs splitting. Load `/refactor` and split by responsibility. If the file genuinely cannot be split (generated parser, indivisible state machine), mark with `// allow: SIZE_OK — <reason>`.\n\n### Smell 2 — Function with more than 3 parameters\n\nMore than 3 arguments signals the function is doing too much, or that related parameters belong in a typed struct. **Workarounds count as the same smell** — passing `dict`/`Record<string, unknown>`/`map[string]any`/`**kwargs`/`...args` to smuggle parameters through one argument, or a throwaway \"config\" object with 6+ fields that exists solely to wrap what would otherwise be positional args (genuine reusable domain types like `HttpClientConfig` are fine).\n\n**When detected:** Group related parameters into a typed value object with a domain name. If 4+ independent inputs are genuinely required, the justification must be SPECIFIC. See [`references/code-smells.md` Smell 2](references/code-smells.md#smell-2--function-with-more-than-3-parameters) for examples in every language.\n\n### Smell 3 — Redundant verification after a destructive action\n\nPerforming a delete/remove/clear/drop and then immediately querying to \"confirm\" the thing is gone. **The operation's contract IS the verification.** Re-checking is AI-generated defensive bloat that wastes cycles and teaches the reader the operation is unreliable — which it is not. Same smell: calling a setter then getting to \"confirm\", writing a file then reading it back, inserting a row then SELECT-ing it, pushing to an array then checking `.length`.\n\n**When detected:** Delete the verification code. Trust the operation's contract. If the operation can genuinely fail silently, fix the operation — do not paper over it with a post-check. See [`references/code-smells.md` Smell 3](references/code-smells.md#smell-3--redundant-verification-after-a-destructive-action) for examples.\n\n### Smell 4 — Negative-form names and conditions\n\nNaming variables, functions, or flags by the **absence** of a quality (`isNotValid`, `noErrors`, `cannotProceed`, `DisableLogging`) instead of its **presence** (`isValid`, `isClean`, `canProceed`, `LoggingEnabled`). Every negation forces the reader to invert mentally; two negations (`if !isNotReady`) become a logic puzzle nobody reviews confidently.\n\n**When detected:** Rename to the positive form and invert the branch logic. Negation IS appropriate in guard clauses (`if !authorized { return }`) and filters (`items.filter(|x| !x.is_expired())`) — the negative form is the intent there. See [`references/code-smells.md` Smell 4](references/code-smells.md#smell-4--negative-form-names-and-conditions) for the full naming table and examples.\n\n---\n\n## LOGGING — CROSS-CUTTING RULES\n\nLogging is part of the code you ship, and it has iron rules of its own: levels chosen by naming the consumer (never by severity vibes), placement at decision points (never inside helpers), stable messages with structured fields — and, above everything else, **the project's existing practice wins: a project with a designated logger gets that logger and nothing else, and a project that does not log does not get logging uninvited.**\n\n**Read [`references/logging.md`](references/logging.md) BEFORE the change** whenever your edit adds or modifies log lines, sets up a logger or a new service entrypoint, or handles errors at a boundary.\n\n---\n\n## MANDATORY POST-WRITE REVIEW LOOP\n\n**This runs EVERY time you finish writing or substantively editing code, before you claim the task is done.** No exceptions.\n\n### Step 1 — measure\n\nFor every file you created or modified:\n\n```bash\nawk '!/^[[:space:]]*$/ && !/^[[:space:]]*(\\/\\/|#|--)/' <file> | wc -l\n```\n\nOr run the per-language checker the skill ships:\n\n```bash\n# Python\nuv run scripts/python/check-no-excuse-rules.py <changed paths>\n# Rust\nbash scripts/rust/check-no-excuse-rules.sh <changed paths>\n# TypeScript\nbun run scripts/typescript/check-no-excuse-rules.ts <changed paths>\n```\n\n### Step 2 — interpret\n\n| Pure LOC | Verdict | Required action |\n|---|---|---|\n| ≤ 200 | Healthy | continue |\n| 200 - 250 | **Warning band** | State that fact and propose a split if the next edit will add lines. |\n| > 250 | **DEFECT** | Do NOT commit new lines to this file. Refactor now: split the touched unit before adding lines, except for rare SIZE_OK or pure-data-table exceptions. |\n\n### Step 3 — architectural self-review (always, even at 80 LOC)\n\nAfter every code-writing session, answer these out loud (in your reply) before declaring done:\n\n1. **Single responsibility?** Can I name what this file owns in one short noun phrase? If the answer needs the word \"and\", split.\n2. **Boundary purity?** Did I parse untrusted input into a typed value at the boundary, or did I pass `dict[str, Any]` / `serde_json::Value` / `unknown` past the boundary? If the latter, fix it.\n3. **Variant discrimination?** Did I use `if`/`elif`/`else` (or `switch` without `assertNever`, or `match` without `assert_never`) anywhere to discriminate on a tagged type or enum? If yes, rewrite as exhaustive match.\n4. **Escape hatches?** Any `Any`, `# type: ignore`, `unwrap`, `expect` outside `main`/tests, `as` numeric cast, `!`, `@ts-ignore`, `@ts-expect-error`, `#[allow]` on a real warning? If yes, fix the type or document why with a comment.\n5. **Defensive layer?** Any null check, try/except, or `isinstance` guarding a value the type system already proves? If yes, delete.\n6. **Helpers for one-off?** Any function, class, or trait introduced for a single caller that will never get a second caller? If yes, inline — axiom 0 should have caught it pre-write; this is the backstop.\n7. **Tests?** Is the behavior I just introduced locked by a test that would fail if I revert this commit?\n8. **Parameter bloat?** Any function I wrote or modified that takes more than 3 parameters — or smuggles them through a dict/kwargs/`...args`/throwaway options object? If yes, group related params into a typed value object. See [Smell 2](references/code-smells.md#smell-2--function-with-more-than-3-parameters).\n9. **Redundant verification?** Did I perform a destructive action (delete, remove, clear) and then immediately re-query to \"confirm\" it worked? Did I call a setter then a getter to \"verify\"? If yes, delete the verification — the operation's contract IS the proof. See [Smell 3](references/code-smells.md#smell-3--redundant-verification-after-a-destructive-action).\n10. **Negative naming?** Any variable, function, or flag named by the absence of a quality (`isNotValid`, `noErrors`, `DisableX`) when a positive name (`isValid`, `isClean`, `EnableX`) would work? If yes, rename to positive form and invert the branch. See [Smell 4](references/code-smells.md#smell-4--negative-form-names-and-conditions).\n11. **Logging?** If I touched log lines, logger setup, or error boundaries: did I follow the project's existing practice (including its absence)? Is every new line leveled by its consumer, placed at a decision point, and message-stable with data in fields? See [`references/logging.md`](references/logging.md).\n\n**If any answer fails, fix it before declaring done.** This loop is the difference between \"the code compiles\" and \"the code is correct.\"\n\n### Step 4 — if you need to refactor right now, invoke the right skill\n\n- Any code smell from the [CODE SMELLS section](#code-smells--automatic-review-triggers) fired (250+ LOC, >3 params, redundant verification, negative naming), or step 3 surfaced more than two issues: **load the `refactor` skill** and execute its safe-refactor protocol (codemap, plan, LSP-driven edits, test after each step). Do not improvise a refactor under time pressure — the refactor skill exists precisely so you do not corrupt behavior while reshaping structure.\n- You inherited a branch with AI-generated patterns (broad `except`, redundant null checks, vague TODOs, oversized modules, dead helpers, redundant post-action verification): **load the `remove-ai-slops` skill** to do a categorized branch-scope cleanup with regression tests pinned first.\n\nThese two skills are not optional cosmetics. They are the recovery path for the smells this loop is designed to catch.\n\n---\n\n## Companion skills - explicit invocation triggers\n\n| Trigger | Skill to load | Why |\n|---|---|---|\n| Any [code smell](#code-smells--automatic-review-triggers) fires (250+ LOC, >3 params, redundant verification), OR the post-write loop surfaces 2+ issues, OR the user says \"reshape this\", \"extract this\", \"clean this up\" | `refactor` | Safe codemap-driven multi-step refactor with LSP + tests after each step. Never improvise a structural change. |\n| Recent branch contains AI-authored patterns (broad except, dead helpers, vague comments, oversized files, redundant post-action verification), OR the user says \"remove slop\", \"clean AI code\", \"deslop\" | `remove-ai-slops` | Tests pinned FIRST, then categorized parallel cleanup, then quality gates. Behavior-preserving. |\n| Rust code touches `unsafe`, `*mut`, `*const`, `MaybeUninit`, FFI, `unsafe impl Send/Sync`, or a custom lock-free primitive | `references/rust-ub/` | Full UB taxonomy + Miri strictness escalation. Every `unsafe` block must survive Miri Level 3 (strict provenance + symbolic alignment + preemption) before it ships. |\n\n---\n\n## Per-language jump table\n\n**Stop. Read the matching reference fully before writing code.**\n\n### Python (`.py`, `.pyi`)\n\n**READ `references/python/README.md` FIRST.** Then load on demand:\n\n| Need | Load |\n|---|---|\n| Strict pyproject.toml / basedpyright / ruff config | `references/python/pyproject-strict.md` |\n| Type patterns (`NewType`, `Final`, `TypeGuard`, `Protocol`) | `references/python/type-patterns.md` |\n| Data modeling (Pydantic vs dataclass vs TypedDict vs StrEnum) | `references/python/data-modeling.md` |\n| Error handling (typed exceptions, exhaustive match, union returns) | `references/python/error-handling.md` |\n| Async with anyio (task groups, cancel scopes, channels) | `references/python/async-anyio.md` |\n| httpx2 production defaults (HTTP/2, brotli+zstd, pool tuning) | `references/python/httpx2-optimization.md` |\n| **orjson** in hot paths (FastAPI integration, Pydantic v2 `model_dump_json` vs orjson, Redis/queue/log) | `references/python/orjson-stack.md` |\n| Data processing with polars + duckdb (NEVER pandas) | `references/python/data-processing.md` |\n| FastAPI + SQLAlchemy 2.x async stack | `references/python/fastapi-stack.md` |\n| pydantic-ai agents | `references/python/pydantic-ai.md` |\n| Textual TUI | `references/python/textual-tui.md` |\n| Disposable PEP 723 scripts | `references/python/one-liners.md` |\n| Canonical library defaults | `references/python/libraries.md` |\n\n### Rust (`.rs`, `Cargo.toml`)\n\n**READ `references/rust/README.md` FIRST.** It defines the five pillars (explicit allocation, compile-time proof, zero hidden cost, type-encoded invariants, deterministic cleanup) and the post-write review checklist. Then load on demand:\n\n| Need | Load |\n|---|---|\n| **Arena allocation, const fn, zero-alloc APIs, bitfield, scopeguard, errdefer, Zig-like patterns** | **`references/rust/zero-cost-safety.md`** |\n| Strict `Cargo.toml` lints + profile + workspace config | `references/rust/cargo-strict.md` |\n| Type-state and newtype patterns (Chris Allen's `Point<Screen>` rule) | `references/rust/type-state.md` |\n| `unsafe` discipline (safe wrapper + SAFETY comment + miri proof) | `references/rust/unsafe-discipline.md` |\n| Async with tokio (JoinSet, cancellation, select, blocking work) | `references/rust/async-tokio.md` |\n| Concurrency primitives (locks, atomics, channels, loom) | `references/rust/concurrency.md` |\n| axum + sqlx + tracing + tower HTTP stack | `references/rust/axum-stack.md` |\n| clap + color-eyre + tracing + indicatif CLI stack | `references/rust/clap-stack.md` |\n| Property tests (proptest) + snapshot tests (insta) | `references/rust/proptest-insta.md` |\n| Disposable `rust-script` scripts | `references/rust/one-liners.md` |\n| Canonical library defaults | `references/rust/libraries.md` |\n| **ANY `unsafe` / FFI / `MaybeUninit` / lock-free work** | **`references/rust-ub/` (full directory)** |\n\n### TypeScript (`.ts`, `.tsx`, `.mts`, `.cts`)\n\n**READ `references/typescript/README.md` FIRST.** Then load on demand:\n\n| Need | Load |\n|---|---|\n| Strict tsconfig + Biome config | `references/typescript/tsconfig-strict.md` |\n| Type patterns (branded types, `as const`, `satisfies`, narrowing, `assertNever`) | `references/typescript/type-patterns.md` |\n| Data modeling (type vs interface vs Zod, readonly, parse-don't-validate) | `references/typescript/data-modeling.md` |\n| Error handling (Result, typed errors, union vs throw, AbortSignal timeouts) | `references/typescript/error-handling.md` |\n| Bootstrapping a new project (Bun, pnpm, Hono, Vite) | `references/typescript/bootstrap.md` |\n| Hono backend stack (hono-openapi, Scalar, Swagger, Zod v4) | `references/typescript/backend-hono.md` |\n\n### Go (`.go`, `go.mod`, `go.sum`, `.golangci.yml`, `*.proto`)\n\n**READ `references/go/README.md` FIRST.** Then load on demand:\n\n| Need | Load |\n|---|---|\n| Library defaults (gin vs chi, sqlc, slog, the 2026 stack reasoning) | `references/go/libraries.md` |\n| Canonical strict `.golangci.yml` (v2) with per-linter rationale | `references/go/golangci-strict.md` |\n| Project layout, Taskfile, CI, `go.mod` template | `references/go/bootstrap.md` |\n| Type patterns (named types, smart constructors, sealed interfaces, generics) | `references/go/type-patterns.md` |\n| Data modeling — the three layers of validation (validator/v10 → smart ctor → sqlc) | `references/go/data-modeling.md` |\n| Error handling (`errors.Is/As`, typed errors, `%w` wrapping, no panic) | `references/go/error-handling.md` |\n| Concurrency (`context.Context`, `errgroup`, channels, locks, `-race`, `goleak`) | `references/go/concurrency.md` |\n| HTTP backend stack (gin + slog + validator + pgx, middleware ordering, SSE, WS) | `references/go/backend-stack.md` |\n| RPC stack (Connect-Go default, grpc-go fallback, protovalidate, Buf) | `references/go/grpc-connect.md` |\n| CLI stack (cobra + slog + huh) | `references/go/cobra-stack.md` |\n| Database stack (sqlc + pgx + goose + testcontainers) | `references/go/sqlc-pgx.md` |\n| TUI stack (bubbletea v2 + bubbles v2 + lipgloss v2; **CJK / IME support**) | `references/go/bubbletea-v2.md` |\n| Testing (Given/When/Then, table-driven, fakes-over-mocks, autogold, rapid) | `references/go/testing.md` |\n| Disposable `go run` scripts | `references/go/one-liners.md` |\n\n---\n\n## Activation\n\nThis skill activates whenever you are writing or modifying any `.py`, `.pyi`, `.rs`, `.ts`, `.tsx`, `.mts`, `.cts`, `.go` file, or any project manifest (`pyproject.toml`, `Cargo.toml`, `package.json`, `tsconfig.json`, `biome.json`, `go.mod`, `go.sum`, `.golangci.yml`, `Taskfile.yml`, `buf.yaml`, `sqlc.yaml`). **Even one-off scripts get the full treatment** - that is the whole point of `uv run` + PEP 723, `rust-script`, `bun run`, and `go run` + `//go:build ignore`: production hygiene with throwaway ergonomics.\n\nThe references contain the recipes. **Read them before writing code. Re-read them when the model drifts.** The post-write review loop is non-negotiable.\n"},"started_at_ms":1789012323394,"completed_at_ms":1789012323479}}
{"timestamp":"2026-09-10T03:52:03.494Z","ordinal":26,"type":"event_msg","payload":{"type":"item_completed","thread_id":"01a08971-6519-7cf3-9399-e7f6b9686fbc","turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","item":{"type":"CommandExecution","id":"exec-766cea05-48fb-4b30-8809-a13ae160bc36","process_id":"37817","command":["/usr/bin/bash","-lc","cat /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/COMPLEX_INTERIOR_PROMPT.md"],"cwd":"file:///lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/kitchen","parsed_cmd":[{"type":"read","cmd":"cat /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/COMPLEX_INTERIOR_PROMPT.md","name":"COMPLEX_INTERIOR_PROMPT.md","path":"/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/COMPLEX_INTERIOR_PROMPT.md"}],"source":"unified_exec_startup","status":"completed","stdout":"# Working restaurant kitchen — production-methodology brief (x86 + GPU)\n\nYou are working end to end and autonomously in this directory as your writable workspace. Do\nnot stop to ask for permission mid-task; this whole task is already authorized. Use whatever\nlocal tools help (shell, Python, Blender's Python API). There is no externally imposed pass\nschedule -- decide your own steps, iterate until the quality bar below is met, then stop.\n\nRead `ENVIRONMENT.md` in this directory first. It records the Blender binary, the GPU\nsituation, and two Cycles denoiser failures that have already cost hours on this exact\nmachine.\n\n## Why this brief exists\n\nA previous run of this methodology built a courtyard house and reached 83.7/100 against a\n90-point gate. Its weakest dimension throughout was **furniture, fixtures and props**: rooms\nwere correctly laid out and correctly lit but read as showroom-empty, and its own reviewers\nkept reporting \"repeated prop arrays\" and \"rigid cloth\". A house lets you get away with that.\nA kitchen in the middle of service does not: density, disorder and wear *are* the subject.\nThis brief is chosen to attack that failure mode, and to stress a completely different\nmaterial and lighting problem from an exterior scene -- brushed and polished stainless under\nmixed artificial light.\n\n## Design brief\n\nDesign and build **a professional restaurant kitchen, mid-service**, as a single fully\nmodelled interior. Roughly 45-60 m², serving a 60-cover restaurant. Not a showroom, not a\ndemonstration kitchen: a working room on a Friday at 20:30.\n\n**The line and the layout.** A hot line with range tops, a salamander, a combi oven, and a\nflat-top; a cold larder/garde-manger section; a pass with heat lamps where plates leave; a\npot-wash corner with a spray arm and racking; dry storage shelving; a walk-in door. Get the\ncirculation right -- chefs must be able to pass behind each other, and the route from line to\npass to service door must be a route, not an obstacle course. Stainless benching throughout,\nwith the undershelf, leg, and adjustable-foot detail that real catering furniture has.\n\n**Extraction and services.** A canopy hood over the line with baffle filters, grease gutter,\nand a drain point. Visible services done honestly: gas manifolds to the burners, water and\nwaste to the sinks, conduit, isolators, a fire-suppression nozzle, a wall-mounted extinguisher\nand a fire blanket. Floor gullies with removable grating. This room is a machine; make the\nmachine legible.\n\n**Density and disorder -- the core of this brief.** The room must be *occupied*. Mise en place\nin labelled gastronorm pans, some full, some nearly out. Stacked plates warming at the pass.\nBlue roll, a squeeze bottle rack, chopping boards colour-coded and stored on edge. Pot racks\nhung with pans that do not all match. A knife roll open on the larder bench. Ticket rail with\npaper dockets at different angles, some torn. Cling film and foil dispensers. Bins with liners\noverfilled slightly. A tea towel over a shoulder-height rail, actually draped. Nothing should\nbe a uniform array: if you place twelve of a thing, twelve is where the eye should stop\nbelieving unless they differ in rotation, wear, contents and fill level. Do not populate the\nroom with human figures -- convey occupancy entirely through the state of the objects.\n\n**Wear, heat and grease.** Stainless does not stay mirror-clean: it takes swirl marks, heat\ntint near burners, water spotting near sinks, and a fine grease film that changes roughness\nmore than colour. Burner grates are carbonised, not black-painted. The floor is non-slip\nquarry tile with grout that has gone dark in the traffic lanes and stayed pale under the\nbenches. Show at least one repair or improvisation -- taped label, wedged shim, replaced\nhandle of the wrong type.\n\n## Material and atmosphere language\n\nDo not leave material choice to chance. Before building, write your own version of this kind\nof language -- specific, named, restrained -- covering every major surface family:\n\n- Stainless steel in at least three distinct states (brushed benching, polished splashback,\n heat-tinted and greased near the line) as genuinely different materials, not one shader\n- Quarry tile floor and its grout, differentiated by traffic\n- Wall finish behind the line vs. elsewhere\n- Plastics: chopping boards, gastronorm lids, squeeze bottles, crates -- each with its own\n translucency and surface\n- Timber where it survives in this environment, and why it looks the way it does\n- Glass, ceramic, and the cloth of towels and aprons\n\nThen write the lighting/atmosphere target explicitly. This scene lives or dies on artificial\nlight: state colour temperatures for the fluorescent/LED ceiling battens, the warmer heat\nlamps at the pass, any under-canopy task lighting, and the glow from open burners and the\ncombi oven's interior. Say how you expect these to conflict -- the mixed-temperature look is\nthe point, and a single flat white ceiling light would fail this brief. Note whether any\ndaylight reaches this room at 20:30 and act accordingly.\n\nSource real PBR textures (diffuse/roughness/normal) for the primary surfaces -- Poly Haven\n(polyhaven.com, CC0, public API) is a good source. Anisotropic response on brushed stainless\nmatters here; if you cannot get it convincing, say so honestly rather than hiding it.\n\n## Geometry and hardware detail\n\nEvery bench, shelf, hinge, castor and bracket must read as a real assembly with real\nthickness. At minimum, somewhere in the kitchen, show: a bench leg with its adjustable foot\nmeeting the floor, a hinge and handle on a fridge or combi door, a shelf bracket actually\ncarrying its shelf, a sink with its waste and trap below, a gas connection at an appliance,\nand the canopy filter housing with removable filters.\n\n## Quality rubric (100 points, exit gate >=90)\n\nScore yourself honestly against this before calling the kitchen done.\n\n| Dimension | Points | Gate |\n|---|---:|---:|\n| **Density, disorder and occupancy** (does it read as mid-service?) | 20 | >=17 |\n| Material language, especially stainless in multiple states | 20 | >=17 |\n| Lighting and atmosphere (mixed sources, believable conflict) | 15 | >=13 |\n| Functional plausibility: circulation, services, code-sense | 15 | >=13 |\n| Geometry and hardware detail (thickness, fixings, services that connect) | 10 | >=8.5 |\n| Wear, heat and grease as distinct, correctly located phenomena | 10 | >=8.5 |\n| Composition of the delivered shots (foreground/midground/background) | 5 | >=4 |\n| Technical quality and portability (clean collections, packed textures, cold start) | 5 | >=4 |\n\n## Multi-cycle review loop\n\nDo not build once and render once. Run at least **4 complete cycles** of: build/change ->\nrender the fixed judgeset (all cameras below) -> inspect the actual pixels (read the rendered\nfiles, don't just trust that code ran) -> score against the rubric -> diagnose specific\nfailures -> fix -> rerender the same cameras to confirm the fix.\n\nFor each cycle, do the pixel review from more than one angle, ideally as genuinely independent\nsub-agents with fresh context, each blind to the others' notes until you synthesize: once for\nfunctional/spatial plausibility, once for material and lighting quality, once for\ncomposition/obstruction problems, and once for technical/geometry cleanliness. **Add a fifth\nlens dedicated solely to occupancy** -- its only job is to ask whether this room looks used,\nand to hunt for repeated arrays, impossibly tidy surfaces, and objects that float, intersect\nor defy gravity. Write down what each lens found before fixing anything.\n\n## Shot list (at least 14)\n\n1. Wide hero along the hot line, canopy overhead, pass beyond\n2. Reverse wide from the service door looking back into the room\n3. The pass, straight on, heat lamps lit, plates waiting\n4. Larder/cold section with mise en place in pans\n5. Pot-wash corner with racking and spray arm\n6. Under the canopy, looking down at the range tops and their grates\n7. Dry storage shelving, showing stock variety and disorder\n8. A working bench surface at eye level -- boards, knife roll, blue roll\n9. Ticket rail and its dockets\n10. Detail: a bench leg, adjustable foot, and floor gully in one frame\n11. Detail: sink, waste, trap, and the wall behind it\n12. Detail: combi oven door hinge, handle, and glass with interior glow\n13. A stainless study -- one frame whose subject is the three states of steel\n14. A material/hardware macro proving the assembly detail above is real\n\nAdd more if a zone needs more than one shot. Compose every principal view with foreground,\nmidground and background structure.\n\n## Rendering\n\nUse Cycles with GPU (OptiX) for every render in the review loop, not just the final pass.\nEnable denoising -- **read ENVIRONMENT.md for which denoiser works here**. Start around 256\nsamples with denoising and adaptive sampling; raise only if you still see noise. Use the AgX\nview transform. An interior lit entirely by small artificial sources, with polished metal\neverywhere, is a hard case: expect fireflies on the specular highlights, and say in\n`RUBRIC_SCORE.md` what sample count and what clamping (if any) you needed.\n\n## Scene organization and portability\n\nOrganize into named Collections. Pack all textures into the `.blend`. Before calling the\nkitchen finished, do a cold-start check: in a *fresh* Blender process, reopen the saved\n`.blend`, rerender one or two judgeset cameras, and confirm they match what you delivered.\n\n## Deliverables\n\n- `kitchen.blend` -- final scene, fully self-contained, GPU-rendered\n- `kitchen.glb` -- portable export\n- `kitchen_plan.png` / `.svg` -- a measured plan of the kitchen with equipment schedule\n- `design_spec.json` -- dimensioned spec (room, benching, appliance schedule, clearances)\n- `renders/` -- the >=14 final renders (numbered, named)\n- `RUBRIC_SCORE.md` -- honest final score per dimension with one-line justifications, plus a\n brief log of what each review cycle found and fixed\n- `SUMMARY.md` -- what you built, materials used, and where to find everything\n","stderr":"","aggregated_output":"# Working restaurant kitchen — production-methodology brief (x86 + GPU)\n\nYou are working end to end and autonomously in this directory as your writable workspace. Do\nnot stop to ask for permission mid-task; this whole task is already authorized. Use whatever\nlocal tools help (shell, Python, Blender's Python API). There is no externally imposed pass\nschedule -- decide your own steps, iterate until the quality bar below is met, then stop.\n\nRead `ENVIRONMENT.md` in this directory first. It records the Blender binary, the GPU\nsituation, and two Cycles denoiser failures that have already cost hours on this exact\nmachine.\n\n## Why this brief exists\n\nA previous run of this methodology built a courtyard house and reached 83.7/100 against a\n90-point gate. Its weakest dimension throughout was **furniture, fixtures and props**: rooms\nwere correctly laid out and correctly lit but read as showroom-empty, and its own reviewers\nkept reporting \"repeated prop arrays\" and \"rigid cloth\". A house lets you get away with that.\nA kitchen in the middle of service does not: density, disorder and wear *are* the subject.\nThis brief is chosen to attack that failure mode, and to stress a completely different\nmaterial and lighting problem from an exterior scene -- brushed and polished stainless under\nmixed artificial light.\n\n## Design brief\n\nDesign and build **a professional restaurant kitchen, mid-service**, as a single fully\nmodelled interior. Roughly 45-60 m², serving a 60-cover restaurant. Not a showroom, not a\ndemonstration kitchen: a working room on a Friday at 20:30.\n\n**The line and the layout.** A hot line with range tops, a salamander, a combi oven, and a\nflat-top; a cold larder/garde-manger section; a pass with heat lamps where plates leave; a\npot-wash corner with a spray arm and racking; dry storage shelving; a walk-in door. Get the\ncirculation right -- chefs must be able to pass behind each other, and the route from line to\npass to service door must be a route, not an obstacle course. Stainless benching throughout,\nwith the undershelf, leg, and adjustable-foot detail that real catering furniture has.\n\n**Extraction and services.** A canopy hood over the line with baffle filters, grease gutter,\nand a drain point. Visible services done honestly: gas manifolds to the burners, water and\nwaste to the sinks, conduit, isolators, a fire-suppression nozzle, a wall-mounted extinguisher\nand a fire blanket. Floor gullies with removable grating. This room is a machine; make the\nmachine legible.\n\n**Density and disorder -- the core of this brief.** The room must be *occupied*. Mise en place\nin labelled gastronorm pans, some full, some nearly out. Stacked plates warming at the pass.\nBlue roll, a squeeze bottle rack, chopping boards colour-coded and stored on edge. Pot racks\nhung with pans that do not all match. A knife roll open on the larder bench. Ticket rail with\npaper dockets at different angles, some torn. Cling film and foil dispensers. Bins with liners\noverfilled slightly. A tea towel over a shoulder-height rail, actually draped. Nothing should\nbe a uniform array: if you place twelve of a thing, twelve is where the eye should stop\nbelieving unless they differ in rotation, wear, contents and fill level. Do not populate the\nroom with human figures -- convey occupancy entirely through the state of the objects.\n\n**Wear, heat and grease.** Stainless does not stay mirror-clean: it takes swirl marks, heat\ntint near burners, water spotting near sinks, and a fine grease film that changes roughness\nmore than colour. Burner grates are carbonised, not black-painted. The floor is non-slip\nquarry tile with grout that has gone dark in the traffic lanes and stayed pale under the\nbenches. Show at least one repair or improvisation -- taped label, wedged shim, replaced\nhandle of the wrong type.\n\n## Material and atmosphere language\n\nDo not leave material choice to chance. Before building, write your own version of this kind\nof language -- specific, named, restrained -- covering every major surface family:\n\n- Stainless steel in at least three distinct states (brushed benching, polished splashback,\n heat-tinted and greased near the line) as genuinely different materials, not one shader\n- Quarry tile floor and its grout, differentiated by traffic\n- Wall finish behind the line vs. elsewhere\n- Plastics: chopping boards, gastronorm lids, squeeze bottles, crates -- each with its own\n translucency and surface\n- Timber where it survives in this environment, and why it looks the way it does\n- Glass, ceramic, and the cloth of towels and aprons\n\nThen write the lighting/atmosphere target explicitly. This scene lives or dies on artificial\nlight: state colour temperatures for the fluorescent/LED ceiling battens, the warmer heat\nlamps at the pass, any under-canopy task lighting, and the glow from open burners and the\ncombi oven's interior. Say how you expect these to conflict -- the mixed-temperature look is\nthe point, and a single flat white ceiling light would fail this brief. Note whether any\ndaylight reaches this room at 20:30 and act accordingly.\n\nSource real PBR textures (diffuse/roughness/normal) for the primary surfaces -- Poly Haven\n(polyhaven.com, CC0, public API) is a good source. Anisotropic response on brushed stainless\nmatters here; if you cannot get it convincing, say so honestly rather than hiding it.\n\n## Geometry and hardware detail\n\nEvery bench, shelf, hinge, castor and bracket must read as a real assembly with real\nthickness. At minimum, somewhere in the kitchen, show: a bench leg with its adjustable foot\nmeeting the floor, a hinge and handle on a fridge or combi door, a shelf bracket actually\ncarrying its shelf, a sink with its waste and trap below, a gas connection at an appliance,\nand the canopy filter housing with removable filters.\n\n## Quality rubric (100 points, exit gate >=90)\n\nScore yourself honestly against this before calling the kitchen done.\n\n| Dimension | Points | Gate |\n|---|---:|---:|\n| **Density, disorder and occupancy** (does it read as mid-service?) | 20 | >=17 |\n| Material language, especially stainless in multiple states | 20 | >=17 |\n| Lighting and atmosphere (mixed sources, believable conflict) | 15 | >=13 |\n| Functional plausibility: circulation, services, code-sense | 15 | >=13 |\n| Geometry and hardware detail (thickness, fixings, services that connect) | 10 | >=8.5 |\n| Wear, heat and grease as distinct, correctly located phenomena | 10 | >=8.5 |\n| Composition of the delivered shots (foreground/midground/background) | 5 | >=4 |\n| Technical quality and portability (clean collections, packed textures, cold start) | 5 | >=4 |\n\n## Multi-cycle review loop\n\nDo not build once and render once. Run at least **4 complete cycles** of: build/change ->\nrender the fixed judgeset (all cameras below) -> inspect the actual pixels (read the rendered\nfiles, don't just trust that code ran) -> score against the rubric -> diagnose specific\nfailures -> fix -> rerender the same cameras to confirm the fix.\n\nFor each cycle, do the pixel review from more than one angle, ideally as genuinely independent\nsub-agents with fresh context, each blind to the others' notes until you synthesize: once for\nfunctional/spatial plausibility, once for material and lighting quality, once for\ncomposition/obstruction problems, and once for technical/geometry cleanliness. **Add a fifth\nlens dedicated solely to occupancy** -- its only job is to ask whether this room looks used,\nand to hunt for repeated arrays, impossibly tidy surfaces, and objects that float, intersect\nor defy gravity. Write down what each lens found before fixing anything.\n\n## Shot list (at least 14)\n\n1. Wide hero along the hot line, canopy overhead, pass beyond\n2. Reverse wide from the service door looking back into the room\n3. The pass, straight on, heat lamps lit, plates waiting\n4. Larder/cold section with mise en place in pans\n5. Pot-wash corner with racking and spray arm\n6. Under the canopy, looking down at the range tops and their grates\n7. Dry storage shelving, showing stock variety and disorder\n8. A working bench surface at eye level -- boards, knife roll, blue roll\n9. Ticket rail and its dockets\n10. Detail: a bench leg, adjustable foot, and floor gully in one frame\n11. Detail: sink, waste, trap, and the wall behind it\n12. Detail: combi oven door hinge, handle, and glass with interior glow\n13. A stainless study -- one frame whose subject is the three states of steel\n14. A material/hardware macro proving the assembly detail above is real\n\nAdd more if a zone needs more than one shot. Compose every principal view with foreground,\nmidground and background structure.\n\n## Rendering\n\nUse Cycles with GPU (OptiX) for every render in the review loop, not just the final pass.\nEnable denoising -- **read ENVIRONMENT.md for which denoiser works here**. Start around 256\nsamples with denoising and adaptive sampling; raise only if you still see noise. Use the AgX\nview transform. An interior lit entirely by small artificial sources, with polished metal\neverywhere, is a hard case: expect fireflies on the specular highlights, and say in\n`RUBRIC_SCORE.md` what sample count and what clamping (if any) you needed.\n\n## Scene organization and portability\n\nOrganize into named Collections. Pack all textures into the `.blend`. Before calling the\nkitchen finished, do a cold-start check: in a *fresh* Blender process, reopen the saved\n`.blend`, rerender one or two judgeset cameras, and confirm they match what you delivered.\n\n## Deliverables\n\n- `kitchen.blend` -- final scene, fully self-contained, GPU-rendered\n- `kitchen.glb` -- portable export\n- `kitchen_plan.png` / `.svg` -- a measured plan of the kitchen with equipment schedule\n- `design_spec.json` -- dimensioned spec (room, benching, appliance schedule, clearances)\n- `renders/` -- the >=14 final renders (numbered, named)\n- `RUBRIC_SCORE.md` -- honest final score per dimension with one-line justifications, plus a\n brief log of what each review cycle found and fixed\n- `SUMMARY.md` -- what you built, materials used, and where to find everything\n","exit_code":0,"duration":{"secs":0,"nanos":82450965},"formatted_output":"# Working restaurant kitchen — production-methodology brief (x86 + GPU)\n\nYou are working end to end and autonomously in this directory as your writable workspace. Do\nnot stop to ask for permission mid-task; this whole task is already authorized. Use whatever\nlocal tools help (shell, Python, Blender's Python API). There is no externally imposed pass\nschedule -- decide your own steps, iterate until the quality bar below is met, then stop.\n\nRead `ENVIRONMENT.md` in this directory first. It records the Blender binary, the GPU\nsituation, and two Cycles denoiser failures that have already cost hours on this exact\nmachine.\n\n## Why this brief exists\n\nA previous run of this methodology built a courtyard house and reached 83.7/100 against a\n90-point gate. Its weakest dimension throughout was **furniture, fixtures and props**: rooms\nwere correctly laid out and correctly lit but read as showroom-empty, and its own reviewers\nkept reporting \"repeated prop arrays\" and \"rigid cloth\". A house lets you get away with that.\nA kitchen in the middle of service does not: density, disorder and wear *are* the subject.\nThis brief is chosen to attack that failure mode, and to stress a completely different\nmaterial and lighting problem from an exterior scene -- brushed and polished stainless under\nmixed artificial light.\n\n## Design brief\n\nDesign and build **a professional restaurant kitchen, mid-service**, as a single fully\nmodelled interior. Roughly 45-60 m², serving a 60-cover restaurant. Not a showroom, not a\ndemonstration kitchen: a working room on a Friday at 20:30.\n\n**The line and the layout.** A hot line with range tops, a salamander, a combi oven, and a\nflat-top; a cold larder/garde-manger section; a pass with heat lamps where plates leave; a\npot-wash corner with a spray arm and racking; dry storage shelving; a walk-in door. Get the\ncirculation right -- chefs must be able to pass behind each other, and the route from line to\npass to service door must be a route, not an obstacle course. Stainless benching throughout,\nwith the undershelf, leg, and adjustable-foot detail that real catering furniture has.\n\n**Extraction and services.** A canopy hood over the line with baffle filters, grease gutter,\nand a drain point. Visible services done honestly: gas manifolds to the burners, water and\nwaste to the sinks, conduit, isolators, a fire-suppression nozzle, a wall-mounted extinguisher\nand a fire blanket. Floor gullies with removable grating. This room is a machine; make the\nmachine legible.\n\n**Density and disorder -- the core of this brief.** The room must be *occupied*. Mise en place\nin labelled gastronorm pans, some full, some nearly out. Stacked plates warming at the pass.\nBlue roll, a squeeze bottle rack, chopping boards colour-coded and stored on edge. Pot racks\nhung with pans that do not all match. A knife roll open on the larder bench. Ticket rail with\npaper dockets at different angles, some torn. Cling film and foil dispensers. Bins with liners\noverfilled slightly. A tea towel over a shoulder-height rail, actually draped. Nothing should\nbe a uniform array: if you place twelve of a thing, twelve is where the eye should stop\nbelieving unless they differ in rotation, wear, contents and fill level. Do not populate the\nroom with human figures -- convey occupancy entirely through the state of the objects.\n\n**Wear, heat and grease.** Stainless does not stay mirror-clean: it takes swirl marks, heat\ntint near burners, water spotting near sinks, and a fine grease film that changes roughness\nmore than colour. Burner grates are carbonised, not black-painted. The floor is non-slip\nquarry tile with grout that has gone dark in the traffic lanes and stayed pale under the\nbenches. Show at least one repair or improvisation -- taped label, wedged shim, replaced\nhandle of the wrong type.\n\n## Material and atmosphere language\n\nDo not leave material choice to chance. Before building, write your own version of this kind\nof language -- specific, named, restrained -- covering every major surface family:\n\n- Stainless steel in at least three distinct states (brushed benching, polished splashback,\n heat-tinted and greased near the line) as genuinely different materials, not one shader\n- Quarry tile floor and its grout, differentiated by traffic\n- Wall finish behind the line vs. elsewhere\n- Plastics: chopping boards, gastronorm lids, squeeze bottles, crates -- each with its own\n translucency and surface\n- Timber where it survives in this environment, and why it looks the way it does\n- Glass, ceramic, and the cloth of towels and aprons\n\nThen write the lighting/atmosphere target explicitly. This scene lives or dies on artificial\nlight: state colour temperatures for the fluorescent/LED ceiling battens, the warmer heat\nlamps at the pass, any under-canopy task lighting, and the glow from open burners and the\ncombi oven's interior. Say how you expect these to conflict -- the mixed-temperature look is\nthe point, and a single flat white ceiling light would fail this brief. Note whether any\ndaylight reaches this room at 20:30 and act accordingly.\n\nSource real PBR textures (diffuse/roughness/normal) for the primary surfaces -- Poly Haven\n(polyhaven.com, CC0, public API) is a good source. Anisotropic response on brushed stainless\nmatters here; if you cannot get it convincing, say so honestly rather than hiding it.\n\n## Geometry and hardware detail\n\nEvery bench, shelf, hinge, castor and bracket must read as a real assembly with real\nthickness. At minimum, somewhere in the kitchen, show: a bench leg with its adjustable foot\nmeeting the floor, a hinge and handle on a fridge or combi door, a shelf bracket actually\ncarrying its shelf, a sink with its waste and trap below, a gas connection at an appliance,\nand the canopy filter housing with removable filters.\n\n## Quality rubric (100 points, exit gate >=90)\n\nScore yourself honestly against this before calling the kitchen done.\n\n| Dimension | Points | Gate |\n|---|---:|---:|\n| **Density, disorder and occupancy** (does it read as mid-service?) | 20 | >=17 |\n| Material language, especially stainless in multiple states | 20 | >=17 |\n| Lighting and atmosphere (mixed sources, believable conflict) | 15 | >=13 |\n| Functional plausibility: circulation, services, code-sense | 15 | >=13 |\n| Geometry and hardware detail (thickness, fixings, services that connect) | 10 | >=8.5 |\n| Wear, heat and grease as distinct, correctly located phenomena | 10 | >=8.5 |\n| Composition of the delivered shots (foreground/midground/background) | 5 | >=4 |\n| Technical quality and portability (clean collections, packed textures, cold start) | 5 | >=4 |\n\n## Multi-cycle review loop\n\nDo not build once and render once. Run at least **4 complete cycles** of: build/change ->\nrender the fixed judgeset (all cameras below) -> inspect the actual pixels (read the rendered\nfiles, don't just trust that code ran) -> score against the rubric -> diagnose specific\nfailures -> fix -> rerender the same cameras to confirm the fix.\n\nFor each cycle, do the pixel review from more than one angle, ideally as genuinely independent\nsub-agents with fresh context, each blind to the others' notes until you synthesize: once for\nfunctional/spatial plausibility, once for material and lighting quality, once for\ncomposition/obstruction problems, and once for technical/geometry cleanliness. **Add a fifth\nlens dedicated solely to occupancy** -- its only job is to ask whether this room looks used,\nand to hunt for repeated arrays, impossibly tidy surfaces, and objects that float, intersect\nor defy gravity. Write down what each lens found before fixing anything.\n\n## Shot list (at least 14)\n\n1. Wide hero along the hot line, canopy overhead, pass beyond\n2. Reverse wide from the service door looking back into the room\n3. The pass, straight on, heat lamps lit, plates waiting\n4. Larder/cold section with mise en place in pans\n5. Pot-wash corner with racking and spray arm\n6. Under the canopy, looking down at the range tops and their grates\n7. Dry storage shelving, showing stock variety and disorder\n8. A working bench surface at eye level -- boards, knife roll, blue roll\n9. Ticket rail and its dockets\n10. Detail: a bench leg, adjustable foot, and floor gully in one frame\n11. Detail: sink, waste, trap, and the wall behind it\n12. Detail: combi oven door hinge, handle, and glass with interior glow\n13. A stainless study -- one frame whose subject is the three states of steel\n14. A material/hardware macro proving the assembly detail above is real\n\nAdd more if a zone needs more than one shot. Compose every principal view with foreground,\nmidground and background structure.\n\n## Rendering\n\nUse Cycles with GPU (OptiX) for every render in the review loop, not just the final pass.\nEnable denoising -- **read ENVIRONMENT.md for which denoiser works here**. Start around 256\nsamples with denoising and adaptive sampling; raise only if you still see noise. Use the AgX\nview transform. An interior lit entirely by small artificial sources, with polished metal\neverywhere, is a hard case: expect fireflies on the specular highlights, and say in\n`RUBRIC_SCORE.md` what sample count and what clamping (if any) you needed.\n\n## Scene organization and portability\n\nOrganize into named Collections. Pack all textures into the `.blend`. Before calling the\nkitchen finished, do a cold-start check: in a *fresh* Blender process, reopen the saved\n`.blend`, rerender one or two judgeset cameras, and confirm they match what you delivered.\n\n## Deliverables\n\n- `kitchen.blend` -- final scene, fully self-contained, GPU-rendered\n- `kitchen.glb` -- portable export\n- `kitchen_plan.png` / `.svg` -- a measured plan of the kitchen with equipment schedule\n- `design_spec.json` -- dimensioned spec (room, benching, appliance schedule, clearances)\n- `renders/` -- the >=14 final renders (numbered, named)\n- `RUBRIC_SCORE.md` -- honest final score per dimension with one-line justifications, plus a\n brief log of what each review cycle found and fixed\n- `SUMMARY.md` -- what you built, materials used, and where to find everything\n"},"started_at_ms":1789012323411,"completed_at_ms":1789012323494}}
单行原文 · 未格式化
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Do\nnot stop to ask for permission mid-task; this whole task is already authorized. Use whatever\nlocal tools help (shell, Python, Blender's Python API). There is no externally imposed pass\nschedule -- decide your own steps, iterate until the quality bar below is met, then stop.\n\nRead `ENVIRONMENT.md` in this directory first. It records the Blender binary, the GPU\nsituation, and two Cycles denoiser failures that have already cost hours on this exact\nmachine.\n\n## Why this brief exists\n\nA previous run of this methodology built a courtyard house and reached 83.7/100 against a\n90-point gate. Its weakest dimension throughout was **furniture, fixtures and props**: rooms\nwere correctly laid out and correctly lit but read as showroom-empty, and its own reviewers\nkept reporting \"repeated prop arrays\" and \"rigid cloth\". A house lets you get away with that.\nA kitchen in the middle of service does not: density, disorder and wear *are* the subject.\nThis brief is chosen to attack that failure mode, and to stress a completely different\nmaterial and lighting problem from an exterior scene -- brushed and polished stainless under\nmixed artificial light.\n\n## Design brief\n\nDesign and build **a professional restaurant kitchen, mid-service**, as a single fully\nmodelled interior. Roughly 45-60 m², serving a 60-cover restaurant. Not a showroom, not a\ndemonstration kitchen: a working room on a Friday at 20:30.\n\n**The line and the layout.** A hot line with range tops, a salamander, a combi oven, and a\nflat-top; a cold larder/garde-manger section; a pass with heat lamps where plates leave; a\npot-wash corner with a spray arm and racking; dry storage shelving; a walk-in door. Get the\ncirculation right -- chefs must be able to pass behind each other, and the route from line to\npass to service door must be a route, not an obstacle course. Stainless benching throughout,\nwith the undershelf, leg, and adjustable-foot detail that real catering furniture has.\n\n**Extraction and services.** A canopy hood over the line with baffle filters, grease gutter,\nand a drain point. Visible services done honestly: gas manifolds to the burners, water and\nwaste to the sinks, conduit, isolators, a fire-suppression nozzle, a wall-mounted extinguisher\nand a fire blanket. Floor gullies with removable grating. This room is a machine; make the\nmachine legible.\n\n**Density and disorder -- the core of this brief.** The room must be *occupied*. Mise en place\nin labelled gastronorm pans, some full, some nearly out. Stacked plates warming at the pass.\nBlue roll, a squeeze bottle rack, chopping boards colour-coded and stored on edge. Pot racks\nhung with pans that do not all match. A knife roll open on the larder bench. Ticket rail with\npaper dockets at different angles, some torn. Cling film and foil dispensers. Bins with liners\noverfilled slightly. A tea towel over a shoulder-height rail, actually draped. Nothing should\nbe a uniform array: if you place twelve of a thing, twelve is where the eye should stop\nbelieving unless they differ in rotation, wear, contents and fill level. Do not populate the\nroom with human figures -- convey occupancy entirely through the state of the objects.\n\n**Wear, heat and grease.** Stainless does not stay mirror-clean: it takes swirl marks, heat\ntint near burners, water spotting near sinks, and a fine grease film that changes roughness\nmore than colour. Burner grates are carbonised, not black-painted. The floor is non-slip\nquarry tile with grout that has gone dark in the traffic lanes and stayed pale under the\nbenches. Show at least one repair or improvisation -- taped label, wedged shim, replaced\nhandle of the wrong type.\n\n## Material and atmosphere language\n\nDo not leave material choice to chance. Before building, write your own version of this kind\nof language -- specific, named, restrained -- covering every major surface family:\n\n- Stainless steel in at least three distinct states (brushed benching, polished splashback,\n heat-tinted and greased near the line) as genuinely different materials, not one shader\n- Quarry tile floor and its grout, differentiated by traffic\n- Wall finish behind the line vs. elsewhere\n- Plastics: chopping boards, gastronorm lids, squeeze bottles, crates -- each with its own\n translucency and surface\n- Timber where it survives in this environment, and why it looks the way it does\n- Glass, ceramic, and the cloth of towels and aprons\n\nThen write the lighting/atmosphere target explicitly. This scene lives or dies on artificial\nlight: state colour temperatures for the fluorescent/LED ceiling battens, the warmer heat\nlamps at the pass, any under-canopy task lighting, and the glow from open burners and the\ncombi oven's interior. Say how you expect these to conflict -- the mixed-temperature look is\nthe point, and a single flat white ceiling light would fail this brief. Note whether any\ndaylight reaches this room at 20:30 and act accordingly.\n\nSource real PBR textures (diffuse/roughness/normal) for the primary surfaces -- Poly Haven\n(polyhaven.com, CC0, public API) is a good source. Anisotropic response on brushed stainless\nmatters here; if you cannot get it convincing, say so honestly rather than hiding it.\n\n## Geometry and hardware detail\n\nEvery bench, shelf, hinge, castor and bracket must read as a real assembly with real\nthickness. At minimum, somewhere in the kitchen, show: a bench leg with its adjustable foot\nmeeting the floor, a hinge and handle on a fridge or combi door, a shelf bracket actually\ncarrying its shelf, a sink with its waste and trap below, a gas connection at an appliance,\nand the canopy filter housing with removable filters.\n\n## Quality rubric (100 points, exit gate >=90)\n\nScore yourself honestly against this before calling the kitchen done.\n\n| Dimension | Points | Gate |\n|---|---:|---:|\n| **Density, disorder and occupancy** (does it read as mid-service?) | 20 | >=17 |\n| Material language, especially stainless in multiple states | 20 | >=17 |\n| Lighting and atmosphere (mixed sources, believable conflict) | 15 | >=13 |\n| Functional plausibility: circulation, services, code-sense | 15 | >=13 |\n| Geometry and hardware detail (thickness, fixings, services that connect) | 10 | >=8.5 |\n| Wear, heat and grease as distinct, correctly located phenomena | 10 | >=8.5 |\n| Composition of the delivered shots (foreground/midground/background) | 5 | >=4 |\n| Technical quality and portability (clean collections, packed textures, cold start) | 5 | >=4 |\n\n## Multi-cycle review loop\n\nDo not build once and render once. Run at least **4 complete cycles** of: build/change ->\nrender the fixed judgeset (all cameras below) -> inspect the actual pixels (read the rendered\nfiles, don't just trust that code ran) -> score against the rubric -> diagnose specific\nfailures -> fix -> rerender the same cameras to confirm the fix.\n\nFor each cycle, do the pixel review from more than one angle, ideally as genuinely independent\nsub-agents with fresh context, each blind to the others' notes until you synthesize: once for\nfunctional/spatial plausibility, once for material and lighting quality, once for\ncomposition/obstruction problems, and once for technical/geometry cleanliness. **Add a fifth\nlens dedicated solely to occupancy** -- its only job is to ask whether this room looks used,\nand to hunt for repeated arrays, impossibly tidy surfaces, and objects that float, intersect\nor defy gravity. Write down what each lens found before fixing anything.\n\n## Shot list (at least 14)\n\n1. Wide hero along the hot line, canopy overhead, pass beyond\n2. Reverse wide from the service door looking back into the room\n3. The pass, straight on, heat lamps lit, plates waiting\n4. Larder/cold section with mise en place in pans\n5. Pot-wash corner with racking and spray arm\n6. Under the canopy, looking down at the range tops and their grates\n7. Dry storage shelving, showing stock variety and disorder\n8. A working bench surface at eye level -- boards, knife roll, blue roll\n9. Ticket rail and its dockets\n10. Detail: a bench leg, adjustable foot, and floor gully in one frame\n11. Detail: sink, waste, trap, and the wall behind it\n12. Detail: combi oven door hinge, handle, and glass with interior glow\n13. A stainless study -- one frame whose subject is the three states of steel\n14. A material/hardware macro proving the assembly detail above is real\n\nAdd more if a zone needs more than one shot. Compose every principal view with foreground,\nmidground and background structure.\n\n## Rendering\n\nUse Cycles with GPU (OptiX) for every render in the review loop, not just the final pass.\nEnable denoising -- **read ENVIRONMENT.md for which denoiser works here**. Start around 256\nsamples with denoising and adaptive sampling; raise only if you still see noise. Use the AgX\nview transform. An interior lit entirely by small artificial sources, with polished metal\neverywhere, is a hard case: expect fireflies on the specular highlights, and say in\n`RUBRIC_SCORE.md` what sample count and what clamping (if any) you needed.\n\n## Scene organization and portability\n\nOrganize into named Collections. Pack all textures into the `.blend`. Before calling the\nkitchen finished, do a cold-start check: in a *fresh* Blender process, reopen the saved\n`.blend`, rerender one or two judgeset cameras, and confirm they match what you delivered.\n\n## Deliverables\n\n- `kitchen.blend` -- final scene, fully self-contained, GPU-rendered\n- `kitchen.glb` -- portable export\n- `kitchen_plan.png` / `.svg` -- a measured plan of the kitchen with equipment schedule\n- `design_spec.json` -- dimensioned spec (room, benching, appliance schedule, clearances)\n- `renders/` -- the >=14 final renders (numbered, named)\n- `RUBRIC_SCORE.md` -- honest final score per dimension with one-line justifications, plus a\n brief log of what each review cycle found and fixed\n- `SUMMARY.md` -- what you built, materials used, and where to find everything\n","stderr":"","aggregated_output":"# Working restaurant kitchen — production-methodology brief (x86 + GPU)\n\nYou are working end to end and autonomously in this directory as your writable workspace. Do\nnot stop to ask for permission mid-task; this whole task is already authorized. Use whatever\nlocal tools help (shell, Python, Blender's Python API). There is no externally imposed pass\nschedule -- decide your own steps, iterate until the quality bar below is met, then stop.\n\nRead `ENVIRONMENT.md` in this directory first. It records the Blender binary, the GPU\nsituation, and two Cycles denoiser failures that have already cost hours on this exact\nmachine.\n\n## Why this brief exists\n\nA previous run of this methodology built a courtyard house and reached 83.7/100 against a\n90-point gate. Its weakest dimension throughout was **furniture, fixtures and props**: rooms\nwere correctly laid out and correctly lit but read as showroom-empty, and its own reviewers\nkept reporting \"repeated prop arrays\" and \"rigid cloth\". A house lets you get away with that.\nA kitchen in the middle of service does not: density, disorder and wear *are* the subject.\nThis brief is chosen to attack that failure mode, and to stress a completely different\nmaterial and lighting problem from an exterior scene -- brushed and polished stainless under\nmixed artificial light.\n\n## Design brief\n\nDesign and build **a professional restaurant kitchen, mid-service**, as a single fully\nmodelled interior. Roughly 45-60 m², serving a 60-cover restaurant. Not a showroom, not a\ndemonstration kitchen: a working room on a Friday at 20:30.\n\n**The line and the layout.** A hot line with range tops, a salamander, a combi oven, and a\nflat-top; a cold larder/garde-manger section; a pass with heat lamps where plates leave; a\npot-wash corner with a spray arm and racking; dry storage shelving; a walk-in door. Get the\ncirculation right -- chefs must be able to pass behind each other, and the route from line to\npass to service door must be a route, not an obstacle course. Stainless benching throughout,\nwith the undershelf, leg, and adjustable-foot detail that real catering furniture has.\n\n**Extraction and services.** A canopy hood over the line with baffle filters, grease gutter,\nand a drain point. Visible services done honestly: gas manifolds to the burners, water and\nwaste to the sinks, conduit, isolators, a fire-suppression nozzle, a wall-mounted extinguisher\nand a fire blanket. Floor gullies with removable grating. This room is a machine; make the\nmachine legible.\n\n**Density and disorder -- the core of this brief.** The room must be *occupied*. Mise en place\nin labelled gastronorm pans, some full, some nearly out. Stacked plates warming at the pass.\nBlue roll, a squeeze bottle rack, chopping boards colour-coded and stored on edge. Pot racks\nhung with pans that do not all match. A knife roll open on the larder bench. Ticket rail with\npaper dockets at different angles, some torn. Cling film and foil dispensers. Bins with liners\noverfilled slightly. A tea towel over a shoulder-height rail, actually draped. Nothing should\nbe a uniform array: if you place twelve of a thing, twelve is where the eye should stop\nbelieving unless they differ in rotation, wear, contents and fill level. Do not populate the\nroom with human figures -- convey occupancy entirely through the state of the objects.\n\n**Wear, heat and grease.** Stainless does not stay mirror-clean: it takes swirl marks, heat\ntint near burners, water spotting near sinks, and a fine grease film that changes roughness\nmore than colour. Burner grates are carbonised, not black-painted. The floor is non-slip\nquarry tile with grout that has gone dark in the traffic lanes and stayed pale under the\nbenches. Show at least one repair or improvisation -- taped label, wedged shim, replaced\nhandle of the wrong type.\n\n## Material and atmosphere language\n\nDo not leave material choice to chance. Before building, write your own version of this kind\nof language -- specific, named, restrained -- covering every major surface family:\n\n- Stainless steel in at least three distinct states (brushed benching, polished splashback,\n heat-tinted and greased near the line) as genuinely different materials, not one shader\n- Quarry tile floor and its grout, differentiated by traffic\n- Wall finish behind the line vs. elsewhere\n- Plastics: chopping boards, gastronorm lids, squeeze bottles, crates -- each with its own\n translucency and surface\n- Timber where it survives in this environment, and why it looks the way it does\n- Glass, ceramic, and the cloth of towels and aprons\n\nThen write the lighting/atmosphere target explicitly. This scene lives or dies on artificial\nlight: state colour temperatures for the fluorescent/LED ceiling battens, the warmer heat\nlamps at the pass, any under-canopy task lighting, and the glow from open burners and the\ncombi oven's interior. Say how you expect these to conflict -- the mixed-temperature look is\nthe point, and a single flat white ceiling light would fail this brief. Note whether any\ndaylight reaches this room at 20:30 and act accordingly.\n\nSource real PBR textures (diffuse/roughness/normal) for the primary surfaces -- Poly Haven\n(polyhaven.com, CC0, public API) is a good source. Anisotropic response on brushed stainless\nmatters here; if you cannot get it convincing, say so honestly rather than hiding it.\n\n## Geometry and hardware detail\n\nEvery bench, shelf, hinge, castor and bracket must read as a real assembly with real\nthickness. At minimum, somewhere in the kitchen, show: a bench leg with its adjustable foot\nmeeting the floor, a hinge and handle on a fridge or combi door, a shelf bracket actually\ncarrying its shelf, a sink with its waste and trap below, a gas connection at an appliance,\nand the canopy filter housing with removable filters.\n\n## Quality rubric (100 points, exit gate >=90)\n\nScore yourself honestly against this before calling the kitchen done.\n\n| Dimension | Points | Gate |\n|---|---:|---:|\n| **Density, disorder and occupancy** (does it read as mid-service?) | 20 | >=17 |\n| Material language, especially stainless in multiple states | 20 | >=17 |\n| Lighting and atmosphere (mixed sources, believable conflict) | 15 | >=13 |\n| Functional plausibility: circulation, services, code-sense | 15 | >=13 |\n| Geometry and hardware detail (thickness, fixings, services that connect) | 10 | >=8.5 |\n| Wear, heat and grease as distinct, correctly located phenomena | 10 | >=8.5 |\n| Composition of the delivered shots (foreground/midground/background) | 5 | >=4 |\n| Technical quality and portability (clean collections, packed textures, cold start) | 5 | >=4 |\n\n## Multi-cycle review loop\n\nDo not build once and render once. Run at least **4 complete cycles** of: build/change ->\nrender the fixed judgeset (all cameras below) -> inspect the actual pixels (read the rendered\nfiles, don't just trust that code ran) -> score against the rubric -> diagnose specific\nfailures -> fix -> rerender the same cameras to confirm the fix.\n\nFor each cycle, do the pixel review from more than one angle, ideally as genuinely independent\nsub-agents with fresh context, each blind to the others' notes until you synthesize: once for\nfunctional/spatial plausibility, once for material and lighting quality, once for\ncomposition/obstruction problems, and once for technical/geometry cleanliness. **Add a fifth\nlens dedicated solely to occupancy** -- its only job is to ask whether this room looks used,\nand to hunt for repeated arrays, impossibly tidy surfaces, and objects that float, intersect\nor defy gravity. Write down what each lens found before fixing anything.\n\n## Shot list (at least 14)\n\n1. Wide hero along the hot line, canopy overhead, pass beyond\n2. Reverse wide from the service door looking back into the room\n3. The pass, straight on, heat lamps lit, plates waiting\n4. Larder/cold section with mise en place in pans\n5. Pot-wash corner with racking and spray arm\n6. Under the canopy, looking down at the range tops and their grates\n7. Dry storage shelving, showing stock variety and disorder\n8. A working bench surface at eye level -- boards, knife roll, blue roll\n9. Ticket rail and its dockets\n10. Detail: a bench leg, adjustable foot, and floor gully in one frame\n11. Detail: sink, waste, trap, and the wall behind it\n12. Detail: combi oven door hinge, handle, and glass with interior glow\n13. A stainless study -- one frame whose subject is the three states of steel\n14. A material/hardware macro proving the assembly detail above is real\n\nAdd more if a zone needs more than one shot. Compose every principal view with foreground,\nmidground and background structure.\n\n## Rendering\n\nUse Cycles with GPU (OptiX) for every render in the review loop, not just the final pass.\nEnable denoising -- **read ENVIRONMENT.md for which denoiser works here**. Start around 256\nsamples with denoising and adaptive sampling; raise only if you still see noise. Use the AgX\nview transform. An interior lit entirely by small artificial sources, with polished metal\neverywhere, is a hard case: expect fireflies on the specular highlights, and say in\n`RUBRIC_SCORE.md` what sample count and what clamping (if any) you needed.\n\n## Scene organization and portability\n\nOrganize into named Collections. Pack all textures into the `.blend`. Before calling the\nkitchen finished, do a cold-start check: in a *fresh* Blender process, reopen the saved\n`.blend`, rerender one or two judgeset cameras, and confirm they match what you delivered.\n\n## Deliverables\n\n- `kitchen.blend` -- final scene, fully self-contained, GPU-rendered\n- `kitchen.glb` -- portable export\n- `kitchen_plan.png` / `.svg` -- a measured plan of the kitchen with equipment schedule\n- `design_spec.json` -- dimensioned spec (room, benching, appliance schedule, clearances)\n- `renders/` -- the >=14 final renders (numbered, named)\n- `RUBRIC_SCORE.md` -- honest final score per dimension with one-line justifications, plus a\n brief log of what each review cycle found and fixed\n- `SUMMARY.md` -- what you built, materials used, and where to find everything\n","exit_code":0,"duration":{"secs":0,"nanos":82450965},"formatted_output":"# Working restaurant kitchen — production-methodology brief (x86 + GPU)\n\nYou are working end to end and autonomously in this directory as your writable workspace. Do\nnot stop to ask for permission mid-task; this whole task is already authorized. Use whatever\nlocal tools help (shell, Python, Blender's Python API). There is no externally imposed pass\nschedule -- decide your own steps, iterate until the quality bar below is met, then stop.\n\nRead `ENVIRONMENT.md` in this directory first. It records the Blender binary, the GPU\nsituation, and two Cycles denoiser failures that have already cost hours on this exact\nmachine.\n\n## Why this brief exists\n\nA previous run of this methodology built a courtyard house and reached 83.7/100 against a\n90-point gate. Its weakest dimension throughout was **furniture, fixtures and props**: rooms\nwere correctly laid out and correctly lit but read as showroom-empty, and its own reviewers\nkept reporting \"repeated prop arrays\" and \"rigid cloth\". A house lets you get away with that.\nA kitchen in the middle of service does not: density, disorder and wear *are* the subject.\nThis brief is chosen to attack that failure mode, and to stress a completely different\nmaterial and lighting problem from an exterior scene -- brushed and polished stainless under\nmixed artificial light.\n\n## Design brief\n\nDesign and build **a professional restaurant kitchen, mid-service**, as a single fully\nmodelled interior. Roughly 45-60 m², serving a 60-cover restaurant. Not a showroom, not a\ndemonstration kitchen: a working room on a Friday at 20:30.\n\n**The line and the layout.** A hot line with range tops, a salamander, a combi oven, and a\nflat-top; a cold larder/garde-manger section; a pass with heat lamps where plates leave; a\npot-wash corner with a spray arm and racking; dry storage shelving; a walk-in door. Get the\ncirculation right -- chefs must be able to pass behind each other, and the route from line to\npass to service door must be a route, not an obstacle course. Stainless benching throughout,\nwith the undershelf, leg, and adjustable-foot detail that real catering furniture has.\n\n**Extraction and services.** A canopy hood over the line with baffle filters, grease gutter,\nand a drain point. Visible services done honestly: gas manifolds to the burners, water and\nwaste to the sinks, conduit, isolators, a fire-suppression nozzle, a wall-mounted extinguisher\nand a fire blanket. Floor gullies with removable grating. This room is a machine; make the\nmachine legible.\n\n**Density and disorder -- the core of this brief.** The room must be *occupied*. Mise en place\nin labelled gastronorm pans, some full, some nearly out. Stacked plates warming at the pass.\nBlue roll, a squeeze bottle rack, chopping boards colour-coded and stored on edge. Pot racks\nhung with pans that do not all match. A knife roll open on the larder bench. Ticket rail with\npaper dockets at different angles, some torn. Cling film and foil dispensers. Bins with liners\noverfilled slightly. A tea towel over a shoulder-height rail, actually draped. Nothing should\nbe a uniform array: if you place twelve of a thing, twelve is where the eye should stop\nbelieving unless they differ in rotation, wear, contents and fill level. Do not populate the\nroom with human figures -- convey occupancy entirely through the state of the objects.\n\n**Wear, heat and grease.** Stainless does not stay mirror-clean: it takes swirl marks, heat\ntint near burners, water spotting near sinks, and a fine grease film that changes roughness\nmore than colour. Burner grates are carbonised, not black-painted. The floor is non-slip\nquarry tile with grout that has gone dark in the traffic lanes and stayed pale under the\nbenches. Show at least one repair or improvisation -- taped label, wedged shim, replaced\nhandle of the wrong type.\n\n## Material and atmosphere language\n\nDo not leave material choice to chance. Before building, write your own version of this kind\nof language -- specific, named, restrained -- covering every major surface family:\n\n- Stainless steel in at least three distinct states (brushed benching, polished splashback,\n heat-tinted and greased near the line) as genuinely different materials, not one shader\n- Quarry tile floor and its grout, differentiated by traffic\n- Wall finish behind the line vs. elsewhere\n- Plastics: chopping boards, gastronorm lids, squeeze bottles, crates -- each with its own\n translucency and surface\n- Timber where it survives in this environment, and why it looks the way it does\n- Glass, ceramic, and the cloth of towels and aprons\n\nThen write the lighting/atmosphere target explicitly. This scene lives or dies on artificial\nlight: state colour temperatures for the fluorescent/LED ceiling battens, the warmer heat\nlamps at the pass, any under-canopy task lighting, and the glow from open burners and the\ncombi oven's interior. Say how you expect these to conflict -- the mixed-temperature look is\nthe point, and a single flat white ceiling light would fail this brief. Note whether any\ndaylight reaches this room at 20:30 and act accordingly.\n\nSource real PBR textures (diffuse/roughness/normal) for the primary surfaces -- Poly Haven\n(polyhaven.com, CC0, public API) is a good source. Anisotropic response on brushed stainless\nmatters here; if you cannot get it convincing, say so honestly rather than hiding it.\n\n## Geometry and hardware detail\n\nEvery bench, shelf, hinge, castor and bracket must read as a real assembly with real\nthickness. At minimum, somewhere in the kitchen, show: a bench leg with its adjustable foot\nmeeting the floor, a hinge and handle on a fridge or combi door, a shelf bracket actually\ncarrying its shelf, a sink with its waste and trap below, a gas connection at an appliance,\nand the canopy filter housing with removable filters.\n\n## Quality rubric (100 points, exit gate >=90)\n\nScore yourself honestly against this before calling the kitchen done.\n\n| Dimension | Points | Gate |\n|---|---:|---:|\n| **Density, disorder and occupancy** (does it read as mid-service?) | 20 | >=17 |\n| Material language, especially stainless in multiple states | 20 | >=17 |\n| Lighting and atmosphere (mixed sources, believable conflict) | 15 | >=13 |\n| Functional plausibility: circulation, services, code-sense | 15 | >=13 |\n| Geometry and hardware detail (thickness, fixings, services that connect) | 10 | >=8.5 |\n| Wear, heat and grease as distinct, correctly located phenomena | 10 | >=8.5 |\n| Composition of the delivered shots (foreground/midground/background) | 5 | >=4 |\n| Technical quality and portability (clean collections, packed textures, cold start) | 5 | >=4 |\n\n## Multi-cycle review loop\n\nDo not build once and render once. Run at least **4 complete cycles** of: build/change ->\nrender the fixed judgeset (all cameras below) -> inspect the actual pixels (read the rendered\nfiles, don't just trust that code ran) -> score against the rubric -> diagnose specific\nfailures -> fix -> rerender the same cameras to confirm the fix.\n\nFor each cycle, do the pixel review from more than one angle, ideally as genuinely independent\nsub-agents with fresh context, each blind to the others' notes until you synthesize: once for\nfunctional/spatial plausibility, once for material and lighting quality, once for\ncomposition/obstruction problems, and once for technical/geometry cleanliness. **Add a fifth\nlens dedicated solely to occupancy** -- its only job is to ask whether this room looks used,\nand to hunt for repeated arrays, impossibly tidy surfaces, and objects that float, intersect\nor defy gravity. Write down what each lens found before fixing anything.\n\n## Shot list (at least 14)\n\n1. Wide hero along the hot line, canopy overhead, pass beyond\n2. Reverse wide from the service door looking back into the room\n3. The pass, straight on, heat lamps lit, plates waiting\n4. Larder/cold section with mise en place in pans\n5. Pot-wash corner with racking and spray arm\n6. Under the canopy, looking down at the range tops and their grates\n7. Dry storage shelving, showing stock variety and disorder\n8. A working bench surface at eye level -- boards, knife roll, blue roll\n9. Ticket rail and its dockets\n10. Detail: a bench leg, adjustable foot, and floor gully in one frame\n11. Detail: sink, waste, trap, and the wall behind it\n12. Detail: combi oven door hinge, handle, and glass with interior glow\n13. A stainless study -- one frame whose subject is the three states of steel\n14. A material/hardware macro proving the assembly detail above is real\n\nAdd more if a zone needs more than one shot. Compose every principal view with foreground,\nmidground and background structure.\n\n## Rendering\n\nUse Cycles with GPU (OptiX) for every render in the review loop, not just the final pass.\nEnable denoising -- **read ENVIRONMENT.md for which denoiser works here**. Start around 256\nsamples with denoising and adaptive sampling; raise only if you still see noise. Use the AgX\nview transform. An interior lit entirely by small artificial sources, with polished metal\neverywhere, is a hard case: expect fireflies on the specular highlights, and say in\n`RUBRIC_SCORE.md` what sample count and what clamping (if any) you needed.\n\n## Scene organization and portability\n\nOrganize into named Collections. Pack all textures into the `.blend`. Before calling the\nkitchen finished, do a cold-start check: in a *fresh* Blender process, reopen the saved\n`.blend`, rerender one or two judgeset cameras, and confirm they match what you delivered.\n\n## Deliverables\n\n- `kitchen.blend` -- final scene, fully self-contained, GPU-rendered\n- `kitchen.glb` -- portable export\n- `kitchen_plan.png` / `.svg` -- a measured plan of the kitchen with equipment schedule\n- `design_spec.json` -- dimensioned spec (room, benching, appliance schedule, clearances)\n- `renders/` -- the >=14 final renders (numbered, named)\n- `RUBRIC_SCORE.md` -- honest final score per dimension with one-line justifications, plus a\n brief log of what each review cycle found and fixed\n- `SUMMARY.md` -- what you built, materials used, and where to find everything\n"},"started_at_ms":1789012323411,"completed_at_ms":1789012323494}}
{"timestamp":"2026-09-10T03:52:03.655Z","ordinal":28,"type":"response_item","payload":{"type":"custom_tool_call_output","id":"ctco_01a08971-ad47-7431-94d0-7f45473a7857","call_id":"call_q8fHtAPokDS1yPVr8vVR7vO4","output":[{"type":"input_text","text":"Script completed\nWall time 0.5 seconds\nOutput:\n"},{"type":"input_text","text":"Warning: truncated output (original token count: 11210)\nTotal output lines: 3\n\n{\"status\":\"fulfilled\",\"value\":{\"chunk_id\":\"f93d15\",\"wall_time_seconds\":0.150141788,\"exit_code\":0,\"original_token_count\":2393,\"output\":\"# /// script\\n# requires-python = \\\">=3.11\\\"\\n# dependencies = []\\n# ///\\n# Run inside Blender 4.5 via build_scene.py.\\n\\\"\\\"\\\"Small Blender construction vocabulary; all dimensions are metres.\\\"\\\"\\\"\\nfrom __future__ import annotations\\nimport math\\nfrom collections.abc import Sequence\\nimport bpy\\nfrom mathutils import Vector\\n\\nVec3 = tuple[float, float, float]\\n\\ndef collection(name: str) -> bpy.types.Collection:\\n col = bpy.data.collections.get(name) or bpy.data.collections.new(name)\\n if col.name not in bpy.context.scene.collection.children:\\n bpy.context.scene.collection.children.link(col)\\n bpy.context.view_layer.active_layer_collection = bpy.context.view_layer.layer_collection.children[col.name]\\n return col\\n\\ndef finish(obj: bpy.types.Object, name: str, mat: bpy.types.Material | None, bevel: float = 0) -> bpy.types.Object:\\n obj.name = name\\n if mat:\\n obj.data.materials.append(mat)\\n if bevel:\\n mod = obj.modifiers.new('Fabricated edge radius', 'BEVEL')\\n mod.width = bevel\\n mod.segments = 3\\n obj.modifiers.new('Weighted corner normals', 'WEIGHTED_NORMAL')\\n return obj\\n\\ndef cube(name: str, loc: Vec3, size: Vec3, mat: bpy.types.Material, bevel: float = .008) -> bpy.types.Object:\\n bpy.ops.mesh.primitive_cube_add(size=1, location=loc)\\n obj = bpy.context.object\\n obj.dimensions = size\\n bpy.ops.object.transform_apply(location=False, rotation=False, scale=True)\\n return finish(obj, name, mat, bevel)\\n\\ndef cyl(name: str, loc: Vec3, radius: float, depth: float, mat: bpy.types.Material, rotation: Vec3 = (0,0,0), vertices: int = 32) -> bpy.types.Object:\\n bpy.ops.mesh.primitive_cylinder_add(vertices=vertices, radius=radius, depth=depth, location=loc, rotation=rotation)\\n obj = finish(bpy.context.object, name, mat, .002)\\n for poly in obj.data.polygons:\\n poly.use_smooth = True\\n return obj\\n\\ndef sphere(name: str, loc: Vec3, scale: Vec3, mat: bpy.types.Material) -> bpy.types.Object:\\n bpy.ops.mesh.primitive_uv_sphere_add(segments=20, ring_count=12, location=loc)\\n obj = bpy.context.object\\n obj.scale = scale\\n for poly in obj.data.polygons:\\n poly.use_smooth = True\\n return finish(obj, name, mat)\\n\\ndef tube(name: str, points: Sequence[Vec3], radius: float, mat: bpy.types.Material) -> bpy.types.Object:\\n curve = bpy.data.curves.new(name, 'CURVE')\\n curve.dimensions = '3D'\\n curve.resolution_u = 16\\n curve.bevel_depth = radius\\n curve.bevel_resolution = 3\\n spline = curve.splines.new('BEZIER')\\n spline.bezier_points.add(len(points)-1)\\n for point, co in zip(spline.bezier_points, points, strict=True):\\n point.co = co\\n point.handle_left_type = 'AUTO'\\n point.handle_right_type = 'AUTO'\\n obj = bpy.data.objects.new(name, curve)\\n bpy.context.collection.objects.link(obj)\\n return finish(obj, name, mat)\\n\\ndef rod(name: str, start: Vec3, end: Vec3, radius: float, mat: bpy.types.Material) -> bpy.types.Object:\\n a, b = Vector(start), Vector(end)\\n obj = cyl(name, tuple((a+b)/2), radius, (b-a).length, mat)\\n obj.rotation_euler = (b-a).to_track_quat('Z','Y').to_euler()\\n return obj\\n\\ndef lathe(name: str, loc: Vec3, profile: Sequence[tuple[float,float]], mat: bpy.types.Material, segments: int = 48) -> bpy.types.Object:\\n verts = [(r*math.cos(i*2*math.pi/segments),r*math.sin(i*2*math.pi/segments),z) for r,z in profile for i in range(segments)]\\n faces = []\\n for j in range(len(profile)-1):\\n for i in range(segments):\\n a=j*segments+i\\n b=j*segments+(i+1)%segments\\n faces.append((a,b,b+segments,a+segments))\\n mesh = bpy.data.meshes.new(name)\\n mesh.from_pydata(verts,[],faces)\\n mesh.update()\\n obj = bpy.data.objects.new(name,mesh)\\n bpy.context.collection.objects.link(obj)\\n obj.location = loc\\n for poly in mesh.polygons:\\n poly.use_smooth=True\\n return finish(obj,name,mat)\\n\\ndef text(name: str, body: str, loc: Vec3, size: float, mat: bpy.types.Material, rotation: Vec3 = (math.pi/2,0,0)) -> bpy.types.Object:\\n curve = bpy.data.curves.new(name, 'FONT')\\n curve.body = body\\n curve.size = size\\n curve.extrude = .00025\\n curve.space_character = 1.12\\n obj=bpy.data.objects.new(name,curve)\\n bpy.context.collection.objects.link(obj)\\n obj.location=loc\\n obj.rotation_euler=rotation\\n return finish(obj,name,mat)\\n\\ndef bench(name: str, x: float, y: float, w: float, d: float, mats: dict[str,bpy.types.Material], z: float = .9) -> None:\\n steel=mats['steel']\\n cube(name+' rolled worktop',(x,y,z-.025),(w,d,.05),steel,.014)\\n cube(name+' front apron',(x,y-d/2+.022,z-.13),(w-.05,.035,.16),steel)\\n cube(name+' undershelf',(x,y,.27),(w-.13,d-.13,.028),steel)\\n for dx in [-w/2+.09,w/2-.09]:\\n for dy in [-d/2+.09,d/2-.09]:\\n cube(name+' tubular leg',(x+dx,y+dy,.49),(.044,.044,.75),steel,.004)\\n cyl(name+' threaded stud',(x+dx,y+dy,.09),.013,.095,steel)\\n for k in range(5):\\n cyl(name+' adjustment thread',(x+dx,y+dy,.06+k*.009),.015,.002,mats['darksteel'])\\n cyl(name+' adjustable nylon foot',(x+dx,y+dy,.028),.033,.036,mats['rubber'])\\n\\ndef area(name: str, loc: Vec3, target: Vec3, energy: float, color: Vec3, size: float, size_y: float | None = None) -> bpy.types.Object:\\n light=bpy.data.lights.new(name,'AREA')\\n light.energy=energy\\n light.color=color\\n light.shape='RECTANGLE'\\n light.size=size\\n light.size_y=size_y or size\\n obj=bpy.data.objects.new(name,light)\\n bpy.context.collection.objects.link(obj)\\n obj.location=loc\\n obj.rotation_euler=(Vector(target)-obj.location).to_track_quat('-Z','Y').to_euler()\\n return obj\\n\\ndef mesh_object(name: str, verts: Sequence[Vec3], faces: Sequence[Sequence[int]], mat: bpy.types.Material) -> bpy.types.Object:\\n mesh=bpy.data.meshes.new(name)\\n mesh.from_pydata(verts,[],faces)\\n mesh.update()\\n obj=bpy.data.objects.new(name,mesh)\\n bpy.context.collection.objects.link(obj)\\n return finish(obj,name,mat)\\n# Friday, 20:30 — material and atmosphere direction\\n\\nA 7.8 × 6.8 × 3.15 m, 53.04 m² working kitchen for 60 covers. Hot line occupies the north wall, cold prep the west, wash the northeast, dry stock the southwest, and the pass the southeast. A 2.8 × 1.1 m central prep table leaves 1.65 m to the hot line, 1.05 m to cold prep, and 1.85 m to wash. Walk-in and service doors open outwards on the south boundary. No people, windows, daylight, or decorative restaurant furniture.\\n\\n## Surface language\\n- **Bench steel / satin 304:** neutral silver, lengthwise anisotropy, fine directional abrasion and oily fingerprints expressed primarily in roughness. Rolled edges and square hollow legs; replaceable nylon levelling feet.\\n- **Splash steel / polished 304:** smoother, softer broad distortions, brighter elongated reflections; physically separate sheet panels with seams and screw heads.\\n- **Line steel / tempered stainless:** warm straw and faint blue heat tint local to hob surrounds; carbonised grates, dark grease roughness on near-burner trays. Never a uniformly orange appliance.\\n- **Quarry tile:** muted iron-red clay, real CC0 terracotta PBR colour/roughness/normal, narrow joints; dark central traffic grout with paler joints below benches. Chips and small damp patches around wash, not a uniformly wet mirror floor.\\n- **Walls:** warm off-white glazed utility tile away from the hot line; larger polished steel panels behind heat. Upper wall is warm chalk paint; olive-grey coving grounds the room.\\n- **Plastics:** scarred opaque red/green/yellow/blue HDPE boards; translucent cloudy GN lids; soft translucent natural squeeze bottles with discoloured sauce levels; rigid matte coloured storage crates.\\n- **Timber:** end-grain bread board and battered supplier crate only, with food-oil darkening and worn edges. No timber worktops.\\n- **Glass:** smoky clear double-glazed combi door, thin bottle glass. Ceramic is warm-white vitrified porcelain with real turned rims and foot rings.\\n- **Cloth:** blue-grey and oat cotton, woven normal, uneven selvedge; gravity-curved towels over rails, a crumpled cloth beside prep, apron hung by its neck loop.\\n\\n## Artificial lighting\\nCeiling battens: 4300 K cool-neutral LEDs, long diffuse sources. Hood task strips: 3300 K. Pass heat lamps: 2400 K amber, concentrated pools on waiting food and porcelain. Active burner tips: blue emissive geometry with subtle local blue light. Combi chamber: 2700 K behind glass. Weak 5000 K spill through service-door porthole is artificial dining/service corridor light. Friday 20:30 contributes no daylight. Warm and cool reflections must cross on satin steel; avoid flat ambient fill.\\n\\n## Assembly and occupancy\\nBench undershelves and levelling feet; detachable hood baffles with rims, gutter and drain; supported wall shelves; plumbed sink and P-trap; gas riser/manifold/hose; detailed oven hinge and wrong replacement handle. Varied pans, partly depleted mise en place, sauce drips, chopped ingredients, dockets, plate stacks, draped cloth and bins tell different work stories. Repetition is restricted to manufactured hardware; hand-placed stock and food receive deterministic variation.\\n\\n## Rendering and evidence\\nAll judgeset images use Cycles OPTIX, 256 samples, adaptive threshold 0.025, OPENIMAGEDENOISE, AgX, indirect clamp 3.0. Persistent scene data enabled. Four full cycles, immutable camera transforms after initial setup. Full-resolution files plus contact sheets are inspected by five separate review lenses. Final portability checked in a fresh Blender process.\\n\"}}\n{\"status\":\"fulfilled\",\"value\":{\"chunk_id\":\"5fa2be\",\"wall_time_seconds\":0.082458175,\"exit_code\":0,\"original_token_count\":2518,\"output\":\"# Working restaurant kitchen — production-methodology brief (x86 + GPU)\\n\\nYou are working end to end and autonomously in this directory as your writable workspace. Do\\nnot stop to ask for permission mid-task; this whole task is already authorized. Use whatever\\nlocal tools help (shell, Python, Blender's Python API). There is no externally imposed pass\\nschedule -- decide your own steps, iterate until the quality bar below is met, then stop.\\n\\nRead `ENVIRONMENT.md` in this directory first. It records the Blender binary, the GPU\\nsituation, and two Cycles denoiser failures that have already cost hours on this exact\\nmachine.\\n\\n## Why this brief exists\\n\\nA previous run of this methodology built a courtyard house and reached 83.7/100 against a\\n90-point gate. Its weakest dimension throughout was **furniture, fixtures and props**: rooms\\nwere correctly laid out and correctly lit but read as showroom-empty, and its own reviewers\\nkept reporting \\\"repeated prop arrays\\\" and \\\"rigid cloth\\\". A house lets you get away with that.\\nA kitchen in the middle of service does not: density, disorder and wear *are* the subject.\\nThis brief is chosen to attack that failure mode, and to stress a completely different\\nmaterial and lighting problem from an exterior scene -- brushed and polished stainless under\\nmixed artificial light.\\n\\n## Design brief\\n\\nDesign and build **a professional restaurant kitchen, mid-service**, as a single fully\\nmodelled interior. Roughly 45-60 m², serving a 60-cover restaurant. Not a showroom, not a\\ndemonstration kitchen: a working room on a Friday at 20:30.\\n\\n**The line and the layout.** A hot line with range tops, a salamander, a combi oven, and a\\nflat-top; a cold larder/garde-manger section; a pass with heat lamps where plates leave; a\\npot-wash corner with a spray arm and racking; dry storage shelving; a walk-in door. Get the\\ncirculation right -- chefs must be able to pass behind each other, and the route from line to\\npass to service door must be a route, not an obstacle course. Stainless benching throughout,\\nwith the undershelf, leg, and adjustable-foot detail that real catering furniture has.\\n\\n**Extraction and services.** A canopy hood over the line with baffle filters, grease gutter,\\nand a drain point. Visible services done honestly: gas manifolds to the burners, water and\\nwaste to the sinks, conduit, isolators, a fire-suppression nozzle, a wall-mounted extinguisher\\nand a fire blanket. Floor gullies with removable grating. This room is a machine; make the\\nmachine legible.\\n\\n**Density and disorder -- the core of this brief.** The room must be *occupied*. Mise en place\\nin labelled gastronorm pans, some full, some nearly out. Stacked plates warming at the pass.\\nBlue roll, a squeeze bottle rack, chopping boards colour-coded and stored on edge. Pot racks\\nhung with pans that do not all match. A knife roll open on the larder bench. Ticket rail with\\npaper dockets at different angles, some torn. Cling film and foil dispensers. Bins with liners\\noverfilled slightly. A tea towel over a shoulder-height rail, actually draped. Nothing should\\nbe a uniform array: if you place twelve of a thing, twelve is where the eye should stop\\nbelieving unless they differ in rotation, wear, contents and fill level. Do not populate the\\nroom with human figures -- convey occupancy entirely through the state of the objects.\\n\\n**Wear, heat and grease.** Stainless does not stay mirror-clean: it takes swirl marks, heat\\ntint near burners, water spotting near sinks, and a fine grease film that changes roughness\\nmore than colour. Burner grates are carbonised, not black-painted. The floor is non-slip\\nquarry tile with grout that has gone dark in the traffic lanes and stayed pale under the\\nbenches. Show at least one repair or improvisation -- taped label, wedged shim, replaced\\nhandle of the wrong type.\\n\\n## Material and atmosphere language\\n\\nDo not leave material choice to chance. Before building, write your own version of this kind\\nof language -- specific, named, restrained -- covering every major surface family:\\n\\n- Stainless steel in at least three distinct states (brushed benching, polished splashback,\\n heat-tinted and greased near the line) as genuinely different materials, not one shader\\n- Quarry tile floor and its grout, differentiated by traffic\\n- Wall finish behind the line vs. elsewhere\\n- Plastics: chopping boards, gastronorm lids, squeeze bottles, crates -- each with its own\\n translucency and surface\\n- Timber where it survives in this environment, and why it looks the way it does\\n- Glass, ceramic, and the cloth of towels and aprons\\n\\nThen write the lighting/atmosphere target explicitly. This scene lives or dies on artificial\\nlight: state colour temperatures for the fluorescent/LED ceiling battens, the warmer heat\\nlamps at the pass, any under-canopy task lighting, and the glow from open burners and the\\ncombi oven's interior. Say how you expect these to conflict -- the mixed-temperature look is\\nthe point, and a single flat white ceiling light would fail this brief. Note whether any\\ndaylight reaches this room at 20:30 and act accordingly.\\n\\nSource real PBR textures (diffuse/roughness/normal) for the primary surfaces -- Poly Haven\\n(polyhaven.com, CC0, public API) is a good source. Anisotropic response on brushed stainless\\nmatters here; if you cannot get it convincing, say so honestly rather than hiding it.\\n\\n## Geometry and hardware detail\\n\\nEvery bench, shelf, hinge, castor and bracket must read as a real assembly with real\\nthickness. At minimum, somewhere in the kitchen, show: a bench leg with its adjustable foot\\nmeeting the floor, a hinge and handle on a fridge or combi door, a shelf bracket actually\\ncarrying its shelf, a sink with its waste and trap below, a gas connection at an appliance,\\nand the canopy filter housing with removable filters.\\n\\n## Quality rubric (100 points, exit gate >=90)\\n\\nScore yourself honestly against this before calling the kitchen done.\\n\\n| Dimension | Points | Gate |\\n|---|---:|---:|\\n| **Density, disorder and occupancy** (does it read as mid-service?) | 20 | >=17 |\\n| Material language, especially stainless in multiple states | 20 | >=17 |\\n| Lighting and atmosphere (mixed sources, believable conflict) | 15 | >=13 |\\n| Functional plausibility: circulation, services, code-sense | 15 | >=13 |\\n| Geometry and hardware detail (thickness, fixings, services that connect) | 10 | >=8.5 |\\n| Wear, heat and grease as distinct, correctly located phenomena | 10 | >=8.5 |\\n| Composition of the delivered shots (foreground/midground/background) | 5 | >=4 |\\n| Technical quality and portability (clean collections, packed textures, cold start) | 5 | >=4 |\\n\\n## Multi-cycle review loop\\n\\nDo not build once and render once. Run at least **4 complete cycles** of: build/change ->\\nrender the fixed judgeset (all cameras below) -> inspect the actual pixels (read the rendered\\nfiles, don't just trust that code ran) -> score against the rubric -> diagnose specific\\nfailures -> fix -> rerender the same cameras to confirm the fix.\\n\\nFor each cycle, do the pixel review from more than one angle, ideally as genuinely independent\\nsub-agents with fresh context, each blind to the others' notes until you synthesize: once for\\nfunctional/spatial plausibility, once for material and lighting quality, once for\\ncomposition/obstruction problems, and once for technical/geometry cleanliness. **Add a fifth\\nlens dedicated solely to occupancy** -- its only job is to ask whether this room looks used,\\nand to hunt for repeated arrays, impossibly tidy surfaces, and objects that float, intersect\\nor defy gravity. Write down what each lens found before fixing anything.\\n\\n## Shot list (at least 14)\\n\\n1. Wide hero along the hot line, canopy overhead, pass beyond\\n2. Reverse wide from the service door looking back into the room\\n3. The pass, straight on, heat lamps lit, plates waiting\\n4. Larder/cold section with mise en place in pans\\n5. Pot-wash corner with racking and spray arm\\n6. Under the canopy, looking down at the range tops and their grates\\n7. Dry storage shelving, showing stock variety and disorder\\n8. A working bench surface at eye level -- boards, knife roll, blue roll\\n9. Ticket rail and its dockets\\n10. Detail: a bench leg, adjustable foot, and floor gully in one frame\\n11. Detail: sink, waste, trap, and the wall behind it\\n12. Detail: combi oven door hinge, handle, and glass with interior glow\\n13. A stainless study -- one frame whose subject is the three states of steel\\n14. A material/hardware macro proving the assembly detail above is real\\n\\nAdd more if a zone needs more than one shot. Compose every principal view with foreground,\\nmidground and background structure.\\n\\n## Rendering\\n\\nUse Cycles with GPU (OptiX) for every render in the review loop, not just the final pass.\\nEnable denoising -- **read ENVIRONMENT.md for which denoiser works here**. Start around 256\\nsamples with denoising and adaptive sampling; raise only if you still see noise. Use the AgX\\nview transform. An interior lit entirely by small artificial sources, with polished metal\\neverywhere, is a hard case: expect fireflies on the specular highlights, and say in\\n`RUBRIC_SCORE.md` what sample count and what clamping (if any) you needed.\\n\\n## Scene organization and portability\\n\\nOrganize into named Collections. Pack all textures into the `.blend`. Before calling the\\nkitchen finished, do a cold-start check: in a *fresh* Blender process, reopen the saved\\n`.blend`, rerender one or two judgeset cameras, and confirm they match what you delivered.\\n\\n## Deliverables\\n\\n- `kitchen.blend` -- final scene, fully self-contained, GPU-rendered\\n- `kitchen.glb` -- portable export\\n- `kitchen_plan.png` / `.svg` -- a measured plan of the kitchen with equipment schedule\\n- `design_spec.json` -- dimensioned spec (room, benching, appliance schedule, clearances)\\n- `renders/` -- the >=14 final rend…1210 tokens truncated…n2. **Parse, don't validate.** Untrusted input crosses a boundary exactly once - at the boundary it is parsed into a typed value (Pydantic v2 in Python, `serde` + `#[derive]` in Rust, Zod in TypeScript). Inside the boundary, code receives typed values and never re-validates. The boundary owns trust; the interior owns logic.\\n\\n3. **One name = one concept.** A `UserId` is not a `string`. A `Seconds` is not a `Milliseconds`. Use `NewType` (Python), newtype tuple structs (Rust), or branded types (TypeScript) for every distinct semantic primitive. The compiler refuses to let two semantic units mix.\\n\\n4. **Exhaustive variant matching, always.** Discriminated unions and enums are matched exhaustively. Python: `match` + `case unreachable: assert_never(unreachable)`. Rust: `match` (the compiler enforces). TypeScript: `switch` + `assertNever`. **`if`/`elif`/`else` is forbidden for discriminating on a tagged variant** - it silently swallows new variants.\\n\\n5. **Trust framework guarantees. Validate only at boundaries.** No null checks for values the type system already proves non-null. No `try/except` around code that cannot raise. No `unwrap`/`!`/`as` to paper over a contract you should have encoded in types. No defensive layer for a scenario you cannot name.\\n\\n6. **Test-driven, with the right shape of test.** No production line ships without a failing test that proves it was needed. Behavior is locked by tests, not by hope. See the TDD discipline below.\\n\\n---\\n\\n## TDD DISCIPLINE — NON-NEGOTIABLE\\n\\n**Every change follows the red → green → refactor loop.** The order is mandatory; reverse it and you have written speculative code.\\n\\n### The order\\n\\n1. **Red.** Write a failing test that names the behavior in `Given / When / Then`. Run it. *Confirm it fails for the right reason* — not a typo, not an import error. A test that fails because the function does not exist yet is the right reason. A test that fails because of a missing import is not.\\n2. **Green.** Write the minimum code to make the test pass. Resist adding the second case until the first passes. The second case is the next red.\\n3. **Refactor.** With the test green, restructure ruthlessly. The test is your safety net. If the test is hard to refactor against, the test is bad — fix the test before the code.\\n\\n### The shape of the test pyramid\\n\\nEvery feature ships with all three rungs, sized in this proportion:\\n\\n| Rung | Count | Purpose | Speed budget |\\n|---|---|---|---|\\n| **Unit** | many | Pure-function correctness for every meaningful input class (happy + edges + boundaries + error paths) | < 10 ms each |\\n| **Integration** | some | The real adapter against the real downstream (DB, queue, HTTP) — via `testcontainers`, `httptest`, or equivalent. NEVER a unit test pretending to be integration. | < 1 s each |\\n| **E2E scenario** | few | One narrative per user-visible outcome. Spins the binary or the full app; drives it through its real surface (HTTP route, CLI invocation, TUI keystroke). Asserts the *observable outcome*, not internal state. | seconds, run on CI |\\n\\nIf a feature has zero E2E coverage, it is undone — even if every unit test passes.\\n\\n### Given / When / Then is mandatory\\n\\nEvery test — unit, integration, E2E — is structured by these three blocks. Names follow `Test_<Behavior>_when_<Condition>` or the language idiom (`it(\\\"<does X> when <Y>\\\")`, `#[test] fn behavior_when_condition`).\\n\\n```\\nGiven: the preconditions and fixtures\\nWhen: the single action under test\\nThen: the observable outcome AND only that outcome\\n```\\n\\nOne `When` per test. Multiple `When`s = multiple tests. The `Then` asserts only what changed because of the `When` — not unrelated invariants.\\n\\n### Less mock, the better\\n\\nMocks are a last resort, not a default. The priority order:\\n\\n1. **Real object.** Use it when constructable in <1 ms (most domain types, pure functions, value objects).\\n2. **In-memory fake.** A real implementation of the interface backed by a map/slice — for stores, caches, queues. The fake has its OWN test that proves it behaves like the real one.\\n3. **Testcontainer / sandbox.** Real Postgres, real Redis, real S3-compatible (MinIO), via `testcontainers`. Slow but truthful.\\n4. **HTTP-level fake.** `httptest.Server` (Go), `respx` (Python), `msw` (TS) — fake at the wire, not at the SDK.\\n5. **Mock.** Only when 1–4 are genuinely infeasible (clock, randomness, external SaaS with no sandbox). Then mock the **narrowest** seam — never an entire service. A mock that returns whatever the test wants is a tautology and proves nothing.\\n\\n**The rule**: if your test fails when the production code's *implementation* changes but its *behavior* did not, the test is over-mocked. Delete the mock; assert on observable outputs.\\n\\n### Efficient AND accurate — both, not either\\n\\n- **Accurate**: the test fails for the bug it names, and only that bug. No incidental coupling to format, ordering, whitespace, or unrelated fields. Assert on the *contract*, not on the dump.\\n- **Efficient**: the whole unit suite runs in < 30 seconds on a developer laptop. The whole integration suite in < 5 minutes. If you cross those budgets, profile and split — fast tests run on every save, slow ones run on push.\\n- **Deterministic**: no `sleep`, no wall-clock dependence, no order dependence (`-shuffle=on`, pytest-randomly, vitest random seed). Inject a `Clock`. Subscribe to the event, do not poll for it. Time-based flake is a bug, not a test issue.\\n- **Isolated**: every test starts from a known fixture and tears down. `t.TempDir()`, `t.Setenv()`, transactional rollback for DB tests. Two tests passing individually but failing together is a fixture leak — fix it immediately.\\n\\n### Prompt tests follow the same rule\\n\\nWhen tests cover LLM prompts or agent outputs, assert on **parsed structure, decisions, or rule data**, never on exact prompt strings. Pinning a sentence is brittle pretend-coverage; asserting that the prompt instructs the model to refuse on category X is real coverage.\\n\\n### Anti-patterns the skill rejects\\n\\n| Anti-pattern | Why it fails | Fix |\\n|---|---|---|\\n| Writing code first, tests \\\"to add later\\\" | Tests-after rationalize the existing design, even when wrong. | Red first. Always. |\\n| One mega-test asserting 12 things | First failure hides the next 11. | Split by `Then` clause — one assertion class per test. |\\n| Mocking every collaborator | Test passes regardless of real behavior. | Use a fake or the real thing. Mock only true unmockables. |\\n| `time.sleep(0.1)` to \\\"let it finish\\\" | Flake guaranteed. | Subscribe to the completion signal; bounded await. |\\n| Snapshot tests for everything | Locks formatting, not behavior. | Snapshots for *structure* (CLI help, JSON shape). Assertions for *behavior*. |\\n| Removing a failing test to \\\"unblock CI\\\" | You just deleted a bug report. | Fix the code or fix the test — never delete to silence. |\\n| `assert result is not None` and stopping there | Passes when result is garbage. | Assert the *value*, not its existence. |\\n| Single happy-path E2E, no edges | Most bugs live on edges. | Edges are unit-test territory — but include at least one E2E that exercises an error path. |\\n\\n---\\n\\n## Cross-language iron list\\n\\nApply unless the per-language reference overrides with something stricter.\\n\\n| Rule | Python | Rust | TypeScript | Go |\\n|---|---|---|---|---|\\n| Immutable by default | `@dataclass(frozen=True, slots=True)` / Pydantic `frozen=True` | every binding is `let` (not `let mut`) unless mutation is the documented purpose | every field is `readonly`; arrays are `readonly T[]` | value types, unexported fields, no mutation methods unless mutation is the purpose |\\n| Branded primitives | `UserId = NewType(\\\"Use…2842 tokens truncated…ng.md) BEFORE the change** whenever your edit adds or modifies log lines, sets up a logger or a new service entrypoint, or handles errors at a boundary.\\n\\n---\\n\\n## MANDATORY POST-WRITE REVIEW LOOP\\n\\n**This runs EVERY time you finish writing or substantively editing code, before you claim the task is done.** No exceptions.\\n\\n### Step 1 — measure\\n\\nFor every file you created or modified:\\n\\n```bash\\nawk '!/^[[:space:]]*$/ && !/^[[:space:]]*(\\\\/\\\\/|#|--)/' <file> | wc -l\\n```\\n\\nOr run the per-language checker the skill ships:\\n\\n```bash\\n# Python\\nuv run scripts/python/check-no-excuse-rules.py <changed paths>\\n# Rust\\nbash scripts/rust/check-no-excuse-rules.sh <changed paths>\\n# TypeScript\\nbun run scripts/typescript/check-no-excuse-rules.ts <changed paths>\\n```\\n\\n### Step 2 — interpret\\n\\n| Pure LOC | Verdict | Required action |\\n|---|---|---|\\n| ≤ 200 | Healthy | continue |\\n| 200 - 250 | **Warning band** | State that fact and propose a split if the next edit will add lines. |\\n| > 250 | **DEFECT** | Do NOT commit new lines to this file. Refactor now: split the touched unit before adding lines, except for rare SIZE_OK or pure-data-table exceptions. |\\n\\n### Step 3 — architectural self-review (always, even at 80 LOC)\\n\\nAfter every code-writing session, answer these out loud (in your reply) before declaring done:\\n\\n1. **Single responsibility?** Can I name what this file owns in one short noun phrase? If the answer needs the word \\\"and\\\", split.\\n2. **Boundary purity?** Did I parse untrusted input into a typed value at the boundary, or did I pass `dict[str, Any]` / `serde_json::Value` / `unknown` past the boundary? If the latter, fix it.\\n3. **Variant discrimination?** Did I use `if`/`elif`/`else` (or `switch` without `assertNever`, or `match` without `assert_never`) anywhere to discriminate on a tagged type or enum? If yes, rewrite as exhaustive match.\\n4. **Escape hatches?** Any `Any`, `# type: ignore`, `unwrap`, `expect` outside `main`/tests, `as` numeric cast, `!`, `@ts-ignore`, `@ts-expect-error`, `#[allow]` on a real warning? If yes, fix the type or document why with a comment.\\n5. **Defensive layer?** Any null check, try/except, or `isinstance` guarding a value the type system already proves? If yes, delete.\\n6. **Helpers for one-off?** Any function, class, or trait introduced for a single caller that will never get a second caller? If yes, inline — axiom 0 should have caught it pre-write; this is the backstop.\\n7. **Tests?** Is the behavior I just introduced locked by a test that would fail if I revert this commit?\\n8. **Parameter bloat?** Any function I wrote or modified that takes more than 3 parameters — or smuggles them through a dict/kwargs/`...args`/throwaway options object? If yes, group related params into a typed value object. See [Smell 2](references/code-smells.md#smell-2--function-with-more-than-3-parameters).\\n9. **Redundant verification?** Did I perform a destructive action (delete, remove, clear) and then immediately re-query to \\\"confirm\\\" it worked? Did I call a setter then a getter to \\\"verify\\\"? If yes, delete the verification — the operation's contract IS the proof. See [Smell 3](references/code-smells.md#smell-3--redundant-verification-after-a-destructive-action).\\n10. **Negative naming?** Any variable, function, or flag named by the absence of a quality (`isNotValid`, `noErrors`, `DisableX`) when a positive name (`isValid`, `isClean`, `EnableX`) would work? If yes, rename to positive form and invert the branch. See [Smell 4](references/code-smells.md#smell-4--negative-form-names-and-conditions).\\n11. **Logging?** If I touched log lines, logger setup, or error boundaries: did I follow the project's existing practice (including its absence)? Is every new line leveled by its consumer, placed at a decision point, and message-stable with data in fields? See [`references/logging.md`](references/logging.md).\\n\\n**If any answer fails, fix it before declaring done.** This loop is the difference between \\\"the code compiles\\\" and \\\"the code is correct.\\\"\\n\\n### Step 4 — if you need to refactor right now, invoke the right skill\\n\\n- Any code smell from the [CODE SMELLS section](#code-smells--automatic-review-triggers) fired (250+ LOC, >3 params, redundant verification, negative naming), or step 3 surfaced more than two issues: **load the `refactor` skill** and execute its safe-refactor protocol (codemap, plan, LSP-driven edits, test after each step). Do not improvise a refactor under time pressure — the refactor skill exists precisely so you do not corrupt behavior while reshaping structure.\\n- You inherited a branch with AI-generated patterns (broad `except`, redundant null checks, vague TODOs, oversized modules, dead helpers, redundant post-action verification): **load the `remove-ai-slops` skill** to do a categorized branch-scope cleanup with regression tests pinned first.\\n\\nThese two skills are not optional cosmetics. They are the recovery path for the smells this loop is designed to catch.\\n\\n---\\n\\n## Companion skills - explicit invocation triggers\\n\\n| Trigger | Skill to load | Why |\\n|---|---|---|\\n| Any [code smell](#code-smells--automatic-review-triggers) fires (250+ LOC, >3 params, redundant verification), OR the post-write loop surfaces 2+ issues, OR the user says \\\"reshape this\\\", \\\"extract this\\\", \\\"clean this up\\\" | `refactor` | Safe codemap-driven multi-step refactor with LSP + tests after each step. Never improvise a structural change. |\\n| Recent branch contains AI-authored patterns (broad except, dead helpers, vague comments, oversized files, redundant post-action verification), OR the user says \\\"remove slop\\\", \\\"clean AI code\\\", \\\"deslop\\\" | `remove-ai-slops` | Tests pinned FIRST, then categorized parallel cleanup, then quality gates. Behavior-preserving. |\\n| Rust code touches `unsafe`, `*mut`, `*const`, `MaybeUninit`, FFI, `unsafe impl Send/Sync`, or a custom lock-free primitive | `references/rust-ub/` | Full UB taxonomy + Miri strictness escalation. Every `unsafe` block must survive Miri Level 3 (strict provenance + symbolic alignment + preemption) before it ships. |\\n\\n---\\n\\n## Per-language jump table\\n\\n**Stop. Read the matching reference fully before writing code.**\\n\\n### Python (`.py`, `.pyi`)\\n\\n**READ `references/python/README.md` FIRST.** Then load on demand:\\n\\n| Need | Load |\\n|---|---|\\n| Strict pyproject.toml / basedpyright / ruff config | `references/python/pyproject-strict.md` |\\n| Type patterns (`NewType`, `Final`, `TypeGuard`, `Protocol`) | `references/python/type-patterns.md` |\\n| Data modeling (Pydantic vs dataclass vs TypedDict vs StrEnum) | `references/python/data-modeling.md` |\\n| Error handling (typed exceptions, exhaustive match, union returns) | `references/python/error-handling.md` |\\n| Async with anyio (task groups, cancel scopes, channels) | `references/python/async-anyio.md` |\\n| httpx2 production defaults (HTTP/2, brotli+zstd, pool tuning) | `references/python/httpx2-optimization.md` |\\n| **orjson** in hot paths (FastAPI integration, Pydantic v2 `model_dump_json` vs orjson, Redis/queue/log) | `references/python/orjson-stack.md` |\\n| Data processing with polars + duckdb (NEVER pandas) | `references/python/data-processing.md` |\\n| FastAPI + SQLAlchemy 2.x async stack | `references/python/fastapi-stack.md` |\\n| pydantic-ai agents | `references/python/pydantic-ai.md` |\\n| Textual TUI | `references/python/textual-tui.md` |\\n| Disposable PEP 723 scripts | `references/python/one-liners.md` |\\n| Canonical library defaults | `references/python/libraries.md` |\\n\\n### Rust (`.rs`, `Cargo.toml`)\\n\\n**READ `references/rust/README.md` FIRST.** It defines the five pillars (explicit allocation, compile-time proof, zero hidden cost, type-encoded invariants, deterministic cleanup) and the post-write review checklist. Then load on demand:\\n\\n| Need | Load |\\n|---|---|\\n| **Arena allocation, const fn, zero-alloc APIs, bitfield, scopeguard, errdefer, Zig-like patterns** | **`references/rust/zero-cost-safety.md`** |\\n| Strict `Cargo.toml` lints + profile + workspace config | `references/rust/cargo-strict.md` |\\n| Type-state and newtype patterns (Chris Allen's `Point<Screen>` rule) | `references/rust/type-state.md` |\\n| `unsafe` discipline (safe wrapper + SAFETY comment + miri proof) | `references/rust/unsafe-discipline.md` |\\n| Async with tokio (JoinSet, cancellation, select, blocking work) | `references/rust/async-tokio.md` |\\n| Concurrency primitives (locks, atomics, channels, loom) | `references/rust/concurrency.md` |\\n| axum + sqlx + tracing + tower HTTP stack | `references/rust/axum-stack.md` |\\n| clap + color-eyre + tracing + indicatif CLI stack | `references/rust/clap-stack.md` |\\n| Property tests (proptest) + snapshot tests (insta) | `references/rust/proptest-insta.md` |\\n| Disposable `rust-script` scripts | `references/rust/one-liners.md` |\\n| Canonical library defaults | `references/rust/libraries.md` |\\n| **ANY `unsafe` / FFI / `MaybeUninit` / lock-free work** | **`references/rust-ub/` (full directory)** |\\n\\n### TypeScript (`.ts`, `.tsx`, `.mts`, `.cts`)\\n\\n**READ `references/typescript/README.md` FIRST.** Then load on demand:\\n\\n| Need | Load |\\n|---|---|\\n| Strict tsconfig + Biome config | `references/typescript/tsconfig-strict.md` |\\n| Type patterns (branded types, `as const`, `satisfies`, narrowing, `assertNever`) | `references/typescript/type-patterns.md` |\\n| Data modeling (type vs interface vs Zod, readonly, parse-don't-validate) | `references/typescript/data-modeling.md` |\\n| Error handling (Result, typed errors, union vs throw, AbortSignal timeouts) | `references/typescript/error-handling.md` |\\n| Bootstrapping a new project (Bun, pnpm, Hono, Vite) | `references/typescript/bootstrap.md` |\\n| Hono backend stack (hono-openapi, Scalar, Swagger, Zod v4) | `references/typescript/backend-hono.md` |\\n\\n### Go (`.go`, `go.mod`, `go.sum`, `.golangci.yml`, `*.proto`)\\n\\n**READ `references/go/README.md` FIRST.** Then load on demand:\\n\\n| Need | Load |\\n|---|---|\\n| Library defaults (gin vs chi, sqlc, slog, the 2026 stack reasoning) | `references/go/libraries.md` |\\n| Canonical strict `.golangci.yml` (v2) with per-linter rationale | `references/go/golangci-strict.md` |\\n| Project layout, Taskfile, CI, `go.mod` template | `references/go/bootstrap.md` |\\n| Type patterns (named types, smart constructors, sealed interfaces, generics) | `references/go/type-patterns.md` |\\n| Data modeling — the three layers of validation (validator/v10 → smart ctor → sqlc) | `references/go/data-modeling.md` |\\n| Error handling (`errors.Is/As`, typed errors, `%w` wrapping, no panic) | `references/go/error-handling.md` |\\n| Concurrency (`context.Context`, `errgroup`, channels, locks, `-race`, `goleak`) | `references/go/concurrency.md` |\\n| HTTP backend stack (gin + slog + validator + pgx, middleware ordering, SSE, WS) | `references/go/backend-stack.md` |\\n| RPC stack (Connect-Go default, grpc-go fallback, protovalidate, Buf) | `references/go/grpc-connect.md` |\\n| CLI stack (cobra + slog + huh) | `references/go/cobra-stack.md` |\\n| Database stack (sqlc + pgx + goose + testcontainers) | `references/go/sqlc-pgx.md` |\\n| TUI stack (bubbletea v2 + bubbles v2 + lipgloss v2; **CJK / IME support**) | `references/go/bubbletea-v2.md` |\\n| Testing (Given/When/Then, table-driven, fakes-over-mocks, autogold, rapid) | `references/go/testing.md` |\\n| Disposable `go run` scripts | `references/go/one-liners.md` |\\n\\n---\\n\\n## Activation\\n\\nThis skill activates whenever you are writing or modifying any `.py`, `.pyi`, `.rs`, `.ts`, `.tsx`, `.mts`, `.cts`, `.go` file, or any project manifest (`pyproject.toml`, `Cargo.toml`, `package.json`, `tsconfig.json`, `biome.json`, `go.mod`, `go.sum`, `.golangci.yml`, `Taskfile.yml`, `buf.yaml`, `sqlc.yaml`). **Even one-off scripts get the full treatment** - that is the whole point of `uv run` + PEP 723, `rust-script`, `bun run`, and `go run` + `//go:build ignore`: production hygiene with throwaway ergonomics.\\n\\nThe references contain the recipes. **Read them before writing code. Re-read them when the model drifts.** The post-write review loop is non-negotiable.\\n\"}}"}],"internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012323.6554484}}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:52:03.655Z","ordinal":28,"type":"response_item","payload":{"type":"custom_tool_call_output","id":"ctco_01a08971-ad47-7431-94d0-7f45473a7857","call_id":"call_q8fHtAPokDS1yPVr8vVR7vO4","output":[{"type":"input_text","text":"Script completed\nWall time 0.5 seconds\nOutput:\n"},{"type":"input_text","text":"Warning: truncated output (original token count: 11210)\nTotal output lines: 3\n\n{\"status\":\"fulfilled\",\"value\":{\"chunk_id\":\"f93d15\",\"wall_time_seconds\":0.150141788,\"exit_code\":0,\"original_token_count\":2393,\"output\":\"# /// script\\n# requires-python = \\\">=3.11\\\"\\n# dependencies = []\\n# ///\\n# Run inside Blender 4.5 via build_scene.py.\\n\\\"\\\"\\\"Small Blender construction vocabulary; all dimensions are metres.\\\"\\\"\\\"\\nfrom __future__ import annotations\\nimport math\\nfrom collections.abc import Sequence\\nimport bpy\\nfrom mathutils import Vector\\n\\nVec3 = tuple[float, float, float]\\n\\ndef collection(name: str) -> bpy.types.Collection:\\n col = bpy.data.collections.get(name) or bpy.data.collections.new(name)\\n if col.name not in bpy.context.scene.collection.children:\\n bpy.context.scene.collection.children.link(col)\\n bpy.context.view_layer.active_layer_collection = bpy.context.view_layer.layer_collection.children[col.name]\\n return col\\n\\ndef finish(obj: bpy.types.Object, name: str, mat: bpy.types.Material | None, bevel: float = 0) -> bpy.types.Object:\\n obj.name = name\\n if mat:\\n obj.data.materials.append(mat)\\n if bevel:\\n mod = obj.modifiers.new('Fabricated edge radius', 'BEVEL')\\n mod.width = bevel\\n mod.segments = 3\\n obj.modifiers.new('Weighted corner normals', 'WEIGHTED_NORMAL')\\n return obj\\n\\ndef cube(name: str, loc: Vec3, size: Vec3, mat: bpy.types.Material, bevel: float = .008) -> bpy.types.Object:\\n bpy.ops.mesh.primitive_cube_add(size=1, location=loc)\\n obj = bpy.context.object\\n obj.dimensions = size\\n bpy.ops.object.transform_apply(location=False, rotation=False, scale=True)\\n return finish(obj, name, mat, bevel)\\n\\ndef cyl(name: str, loc: Vec3, radius: float, depth: float, mat: bpy.types.Material, rotation: Vec3 = (0,0,0), vertices: int = 32) -> bpy.types.Object:\\n bpy.ops.mesh.primitive_cylinder_add(vertices=vertices, radius=radius, depth=depth, location=loc, rotation=rotation)\\n obj = finish(bpy.context.object, name, mat, .002)\\n for poly in obj.data.polygons:\\n poly.use_smooth = True\\n return obj\\n\\ndef sphere(name: str, loc: Vec3, scale: Vec3, mat: bpy.types.Material) -> bpy.types.Object:\\n bpy.ops.mesh.primitive_uv_sphere_add(segments=20, ring_count=12, location=loc)\\n obj = bpy.context.object\\n obj.scale = scale\\n for poly in obj.data.polygons:\\n poly.use_smooth = True\\n return finish(obj, name, mat)\\n\\ndef tube(name: str, points: Sequence[Vec3], radius: float, mat: bpy.types.Material) -> bpy.types.Object:\\n curve = bpy.data.curves.new(name, 'CURVE')\\n curve.dimensions = '3D'\\n curve.resolution_u = 16\\n curve.bevel_depth = radius\\n curve.bevel_resolution = 3\\n spline = curve.splines.new('BEZIER')\\n spline.bezier_points.add(len(points)-1)\\n for point, co in zip(spline.bezier_points, points, strict=True):\\n point.co = co\\n point.handle_left_type = 'AUTO'\\n point.handle_right_type = 'AUTO'\\n obj = bpy.data.objects.new(name, curve)\\n bpy.context.collection.objects.link(obj)\\n return finish(obj, name, mat)\\n\\ndef rod(name: str, start: Vec3, end: Vec3, radius: float, mat: bpy.types.Material) -> bpy.types.Object:\\n a, b = Vector(start), Vector(end)\\n obj = cyl(name, tuple((a+b)/2), radius, (b-a).length, mat)\\n obj.rotation_euler = (b-a).to_track_quat('Z','Y').to_euler()\\n return obj\\n\\ndef lathe(name: str, loc: Vec3, profile: Sequence[tuple[float,float]], mat: bpy.types.Material, segments: int = 48) -> bpy.types.Object:\\n verts = [(r*math.cos(i*2*math.pi/segments),r*math.sin(i*2*math.pi/segments),z) for r,z in profile for i in range(segments)]\\n faces = []\\n for j in range(len(profile)-1):\\n for i in range(segments):\\n a=j*segments+i\\n b=j*segments+(i+1)%segments\\n faces.append((a,b,b+segments,a+segments))\\n mesh = bpy.data.meshes.new(name)\\n mesh.from_pydata(verts,[],faces)\\n mesh.update()\\n obj = bpy.data.objects.new(name,mesh)\\n bpy.context.collection.objects.link(obj)\\n obj.location = loc\\n for poly in mesh.polygons:\\n poly.use_smooth=True\\n return finish(obj,name,mat)\\n\\ndef text(name: str, body: str, loc: Vec3, size: float, mat: bpy.types.Material, rotation: Vec3 = (math.pi/2,0,0)) -> bpy.types.Object:\\n curve = bpy.data.curves.new(name, 'FONT')\\n curve.body = body\\n curve.size = size\\n curve.extrude = .00025\\n curve.space_character = 1.12\\n obj=bpy.data.objects.new(name,curve)\\n bpy.context.collection.objects.link(obj)\\n obj.location=loc\\n obj.rotation_euler=rotation\\n return finish(obj,name,mat)\\n\\ndef bench(name: str, x: float, y: float, w: float, d: float, mats: dict[str,bpy.types.Material], z: float = .9) -> None:\\n steel=mats['steel']\\n cube(name+' rolled worktop',(x,y,z-.025),(w,d,.05),steel,.014)\\n cube(name+' front apron',(x,y-d/2+.022,z-.13),(w-.05,.035,.16),steel)\\n cube(name+' undershelf',(x,y,.27),(w-.13,d-.13,.028),steel)\\n for dx in [-w/2+.09,w/2-.09]:\\n for dy in [-d/2+.09,d/2-.09]:\\n cube(name+' tubular leg',(x+dx,y+dy,.49),(.044,.044,.75),steel,.004)\\n cyl(name+' threaded stud',(x+dx,y+dy,.09),.013,.095,steel)\\n for k in range(5):\\n cyl(name+' adjustment thread',(x+dx,y+dy,.06+k*.009),.015,.002,mats['darksteel'])\\n cyl(name+' adjustable nylon foot',(x+dx,y+dy,.028),.033,.036,mats['rubber'])\\n\\ndef area(name: str, loc: Vec3, target: Vec3, energy: float, color: Vec3, size: float, size_y: float | None = None) -> bpy.types.Object:\\n light=bpy.data.lights.new(name,'AREA')\\n light.energy=energy\\n light.color=color\\n light.shape='RECTANGLE'\\n light.size=size\\n light.size_y=size_y or size\\n obj=bpy.data.objects.new(name,light)\\n bpy.context.collection.objects.link(obj)\\n obj.location=loc\\n obj.rotation_euler=(Vector(target)-obj.location).to_track_quat('-Z','Y').to_euler()\\n return obj\\n\\ndef mesh_object(name: str, verts: Sequence[Vec3], faces: Sequence[Sequence[int]], mat: bpy.types.Material) -> bpy.types.Object:\\n mesh=bpy.data.meshes.new(name)\\n mesh.from_pydata(verts,[],faces)\\n mesh.update()\\n obj=bpy.data.objects.new(name,mesh)\\n bpy.context.collection.objects.link(obj)\\n return finish(obj,name,mat)\\n# Friday, 20:30 — material and atmosphere direction\\n\\nA 7.8 × 6.8 × 3.15 m, 53.04 m² working kitchen for 60 covers. Hot line occupies the north wall, cold prep the west, wash the northeast, dry stock the southwest, and the pass the southeast. A 2.8 × 1.1 m central prep table leaves 1.65 m to the hot line, 1.05 m to cold prep, and 1.85 m to wash. Walk-in and service doors open outwards on the south boundary. No people, windows, daylight, or decorative restaurant furniture.\\n\\n## Surface language\\n- **Bench steel / satin 304:** neutral silver, lengthwise anisotropy, fine directional abrasion and oily fingerprints expressed primarily in roughness. Rolled edges and square hollow legs; replaceable nylon levelling feet.\\n- **Splash steel / polished 304:** smoother, softer broad distortions, brighter elongated reflections; physically separate sheet panels with seams and screw heads.\\n- **Line steel / tempered stainless:** warm straw and faint blue heat tint local to hob surrounds; carbonised grates, dark grease roughness on near-burner trays. Never a uniformly orange appliance.\\n- **Quarry tile:** muted iron-red clay, real CC0 terracotta PBR colour/roughness/normal, narrow joints; dark central traffic grout with paler joints below benches. Chips and small damp patches around wash, not a uniformly wet mirror floor.\\n- **Walls:** warm off-white glazed utility tile away from the hot line; larger polished steel panels behind heat. Upper wall is warm chalk paint; olive-grey coving grounds the room.\\n- **Plastics:** scarred opaque red/green/yellow/blue HDPE boards; translucent cloudy GN lids; soft translucent natural squeeze bottles with discoloured sauce levels; rigid matte coloured storage crates.\\n- **Timber:** end-grain bread board and battered supplier crate only, with food-oil darkening and worn edges. No timber worktops.\\n- **Glass:** smoky clear double-glazed combi door, thin bottle glass. Ceramic is warm-white vitrified porcelain with real turned rims and foot rings.\\n- **Cloth:** blue-grey and oat cotton, woven normal, uneven selvedge; gravity-curved towels over rails, a crumpled cloth beside prep, apron hung by its neck loop.\\n\\n## Artificial lighting\\nCeiling battens: 4300 K cool-neutral LEDs, long diffuse sources. Hood task strips: 3300 K. Pass heat lamps: 2400 K amber, concentrated pools on waiting food and porcelain. Active burner tips: blue emissive geometry with subtle local blue light. Combi chamber: 2700 K behind glass. Weak 5000 K spill through service-door porthole is artificial dining/service corridor light. Friday 20:30 contributes no daylight. Warm and cool reflections must cross on satin steel; avoid flat ambient fill.\\n\\n## Assembly and occupancy\\nBench undershelves and levelling feet; detachable hood baffles with rims, gutter and drain; supported wall shelves; plumbed sink and P-trap; gas riser/manifold/hose; detailed oven hinge and wrong replacement handle. Varied pans, partly depleted mise en place, sauce drips, chopped ingredients, dockets, plate stacks, draped cloth and bins tell different work stories. Repetition is restricted to manufactured hardware; hand-placed stock and food receive deterministic variation.\\n\\n## Rendering and evidence\\nAll judgeset images use Cycles OPTIX, 256 samples, adaptive threshold 0.025, OPENIMAGEDENOISE, AgX, indirect clamp 3.0. Persistent scene data enabled. Four full cycles, immutable camera transforms after initial setup. Full-resolution files plus contact sheets are inspected by five separate review lenses. Final portability checked in a fresh Blender process.\\n\"}}\n{\"status\":\"fulfilled\",\"value\":{\"chunk_id\":\"5fa2be\",\"wall_time_seconds\":0.082458175,\"exit_code\":0,\"original_token_count\":2518,\"output\":\"# Working restaurant kitchen — production-methodology brief (x86 + GPU)\\n\\nYou are working end to end and autonomously in this directory as your writable workspace. Do\\nnot stop to ask for permission mid-task; this whole task is already authorized. Use whatever\\nlocal tools help (shell, Python, Blender's Python API). There is no externally imposed pass\\nschedule -- decide your own steps, iterate until the quality bar below is met, then stop.\\n\\nRead `ENVIRONMENT.md` in this directory first. It records the Blender binary, the GPU\\nsituation, and two Cycles denoiser failures that have already cost hours on this exact\\nmachine.\\n\\n## Why this brief exists\\n\\nA previous run of this methodology built a courtyard house and reached 83.7/100 against a\\n90-point gate. Its weakest dimension throughout was **furniture, fixtures and props**: rooms\\nwere correctly laid out and correctly lit but read as showroom-empty, and its own reviewers\\nkept reporting \\\"repeated prop arrays\\\" and \\\"rigid cloth\\\". A house lets you get away with that.\\nA kitchen in the middle of service does not: density, disorder and wear *are* the subject.\\nThis brief is chosen to attack that failure mode, and to stress a completely different\\nmaterial and lighting problem from an exterior scene -- brushed and polished stainless under\\nmixed artificial light.\\n\\n## Design brief\\n\\nDesign and build **a professional restaurant kitchen, mid-service**, as a single fully\\nmodelled interior. Roughly 45-60 m², serving a 60-cover restaurant. Not a showroom, not a\\ndemonstration kitchen: a working room on a Friday at 20:30.\\n\\n**The line and the layout.** A hot line with range tops, a salamander, a combi oven, and a\\nflat-top; a cold larder/garde-manger section; a pass with heat lamps where plates leave; a\\npot-wash corner with a spray arm and racking; dry storage shelving; a walk-in door. Get the\\ncirculation right -- chefs must be able to pass behind each other, and the route from line to\\npass to service door must be a route, not an obstacle course. Stainless benching throughout,\\nwith the undershelf, leg, and adjustable-foot detail that real catering furniture has.\\n\\n**Extraction and services.** A canopy hood over the line with baffle filters, grease gutter,\\nand a drain point. Visible services done honestly: gas manifolds to the burners, water and\\nwaste to the sinks, conduit, isolators, a fire-suppression nozzle, a wall-mounted extinguisher\\nand a fire blanket. Floor gullies with removable grating. This room is a machine; make the\\nmachine legible.\\n\\n**Density and disorder -- the core of this brief.** The room must be *occupied*. Mise en place\\nin labelled gastronorm pans, some full, some nearly out. Stacked plates warming at the pass.\\nBlue roll, a squeeze bottle rack, chopping boards colour-coded and stored on edge. Pot racks\\nhung with pans that do not all match. A knife roll open on the larder bench. Ticket rail with\\npaper dockets at different angles, some torn. Cling film and foil dispensers. Bins with liners\\noverfilled slightly. A tea towel over a shoulder-height rail, actually draped. Nothing should\\nbe a uniform array: if you place twelve of a thing, twelve is where the eye should stop\\nbelieving unless they differ in rotation, wear, contents and fill level. Do not populate the\\nroom with human figures -- convey occupancy entirely through the state of the objects.\\n\\n**Wear, heat and grease.** Stainless does not stay mirror-clean: it takes swirl marks, heat\\ntint near burners, water spotting near sinks, and a fine grease film that changes roughness\\nmore than colour. Burner grates are carbonised, not black-painted. The floor is non-slip\\nquarry tile with grout that has gone dark in the traffic lanes and stayed pale under the\\nbenches. Show at least one repair or improvisation -- taped label, wedged shim, replaced\\nhandle of the wrong type.\\n\\n## Material and atmosphere language\\n\\nDo not leave material choice to chance. Before building, write your own version of this kind\\nof language -- specific, named, restrained -- covering every major surface family:\\n\\n- Stainless steel in at least three distinct states (brushed benching, polished splashback,\\n heat-tinted and greased near the line) as genuinely different materials, not one shader\\n- Quarry tile floor and its grout, differentiated by traffic\\n- Wall finish behind the line vs. elsewhere\\n- Plastics: chopping boards, gastronorm lids, squeeze bottles, crates -- each with its own\\n translucency and surface\\n- Timber where it survives in this environment, and why it looks the way it does\\n- Glass, ceramic, and the cloth of towels and aprons\\n\\nThen write the lighting/atmosphere target explicitly. This scene lives or dies on artificial\\nlight: state colour temperatures for the fluorescent/LED ceiling battens, the warmer heat\\nlamps at the pass, any under-canopy task lighting, and the glow from open burners and the\\ncombi oven's interior. Say how you expect these to conflict -- the mixed-temperature look is\\nthe point, and a single flat white ceiling light would fail this brief. Note whether any\\ndaylight reaches this room at 20:30 and act accordingly.\\n\\nSource real PBR textures (diffuse/roughness/normal) for the primary surfaces -- Poly Haven\\n(polyhaven.com, CC0, public API) is a good source. Anisotropic response on brushed stainless\\nmatters here; if you cannot get it convincing, say so honestly rather than hiding it.\\n\\n## Geometry and hardware detail\\n\\nEvery bench, shelf, hinge, castor and bracket must read as a real assembly with real\\nthickness. At minimum, somewhere in the kitchen, show: a bench leg with its adjustable foot\\nmeeting the floor, a hinge and handle on a fridge or combi door, a shelf bracket actually\\ncarrying its shelf, a sink with its waste and trap below, a gas connection at an appliance,\\nand the canopy filter housing with removable filters.\\n\\n## Quality rubric (100 points, exit gate >=90)\\n\\nScore yourself honestly against this before calling the kitchen done.\\n\\n| Dimension | Points | Gate |\\n|---|---:|---:|\\n| **Density, disorder and occupancy** (does it read as mid-service?) | 20 | >=17 |\\n| Material language, especially stainless in multiple states | 20 | >=17 |\\n| Lighting and atmosphere (mixed sources, believable conflict) | 15 | >=13 |\\n| Functional plausibility: circulation, services, code-sense | 15 | >=13 |\\n| Geometry and hardware detail (thickness, fixings, services that connect) | 10 | >=8.5 |\\n| Wear, heat and grease as distinct, correctly located phenomena | 10 | >=8.5 |\\n| Composition of the delivered shots (foreground/midground/background) | 5 | >=4 |\\n| Technical quality and portability (clean collections, packed textures, cold start) | 5 | >=4 |\\n\\n## Multi-cycle review loop\\n\\nDo not build once and render once. Run at least **4 complete cycles** of: build/change ->\\nrender the fixed judgeset (all cameras below) -> inspect the actual pixels (read the rendered\\nfiles, don't just trust that code ran) -> score against the rubric -> diagnose specific\\nfailures -> fix -> rerender the same cameras to confirm the fix.\\n\\nFor each cycle, do the pixel review from more than one angle, ideally as genuinely independent\\nsub-agents with fresh context, each blind to the others' notes until you synthesize: once for\\nfunctional/spatial plausibility, once for material and lighting quality, once for\\ncomposition/obstruction problems, and once for technical/geometry cleanliness. **Add a fifth\\nlens dedicated solely to occupancy** -- its only job is to ask whether this room looks used,\\nand to hunt for repeated arrays, impossibly tidy surfaces, and objects that float, intersect\\nor defy gravity. Write down what each lens found before fixing anything.\\n\\n## Shot list (at least 14)\\n\\n1. Wide hero along the hot line, canopy overhead, pass beyond\\n2. Reverse wide from the service door looking back into the room\\n3. The pass, straight on, heat lamps lit, plates waiting\\n4. Larder/cold section with mise en place in pans\\n5. Pot-wash corner with racking and spray arm\\n6. Under the canopy, looking down at the range tops and their grates\\n7. Dry storage shelving, showing stock variety and disorder\\n8. A working bench surface at eye level -- boards, knife roll, blue roll\\n9. Ticket rail and its dockets\\n10. Detail: a bench leg, adjustable foot, and floor gully in one frame\\n11. Detail: sink, waste, trap, and the wall behind it\\n12. Detail: combi oven door hinge, handle, and glass with interior glow\\n13. A stainless study -- one frame whose subject is the three states of steel\\n14. A material/hardware macro proving the assembly detail above is real\\n\\nAdd more if a zone needs more than one shot. Compose every principal view with foreground,\\nmidground and background structure.\\n\\n## Rendering\\n\\nUse Cycles with GPU (OptiX) for every render in the review loop, not just the final pass.\\nEnable denoising -- **read ENVIRONMENT.md for which denoiser works here**. Start around 256\\nsamples with denoising and adaptive sampling; raise only if you still see noise. Use the AgX\\nview transform. An interior lit entirely by small artificial sources, with polished metal\\neverywhere, is a hard case: expect fireflies on the specular highlights, and say in\\n`RUBRIC_SCORE.md` what sample count and what clamping (if any) you needed.\\n\\n## Scene organization and portability\\n\\nOrganize into named Collections. Pack all textures into the `.blend`. Before calling the\\nkitchen finished, do a cold-start check: in a *fresh* Blender process, reopen the saved\\n`.blend`, rerender one or two judgeset cameras, and confirm they match what you delivered.\\n\\n## Deliverables\\n\\n- `kitchen.blend` -- final scene, fully self-contained, GPU-rendered\\n- `kitchen.glb` -- portable export\\n- `kitchen_plan.png` / `.svg` -- a measured plan of the kitchen with equipment schedule\\n- `design_spec.json` -- dimensioned spec (room, benching, appliance schedule, clearances)\\n- `renders/` -- the >=14 final rend…1210 tokens truncated…n2. **Parse, don't validate.** Untrusted input crosses a boundary exactly once - at the boundary it is parsed into a typed value (Pydantic v2 in Python, `serde` + `#[derive]` in Rust, Zod in TypeScript). Inside the boundary, code receives typed values and never re-validates. The boundary owns trust; the interior owns logic.\\n\\n3. **One name = one concept.** A `UserId` is not a `string`. A `Seconds` is not a `Milliseconds`. Use `NewType` (Python), newtype tuple structs (Rust), or branded types (TypeScript) for every distinct semantic primitive. The compiler refuses to let two semantic units mix.\\n\\n4. **Exhaustive variant matching, always.** Discriminated unions and enums are matched exhaustively. Python: `match` + `case unreachable: assert_never(unreachable)`. Rust: `match` (the compiler enforces). TypeScript: `switch` + `assertNever`. **`if`/`elif`/`else` is forbidden for discriminating on a tagged variant** - it silently swallows new variants.\\n\\n5. **Trust framework guarantees. Validate only at boundaries.** No null checks for values the type system already proves non-null. No `try/except` around code that cannot raise. No `unwrap`/`!`/`as` to paper over a contract you should have encoded in types. No defensive layer for a scenario you cannot name.\\n\\n6. **Test-driven, with the right shape of test.** No production line ships without a failing test that proves it was needed. Behavior is locked by tests, not by hope. See the TDD discipline below.\\n\\n---\\n\\n## TDD DISCIPLINE — NON-NEGOTIABLE\\n\\n**Every change follows the red → green → refactor loop.** The order is mandatory; reverse it and you have written speculative code.\\n\\n### The order\\n\\n1. **Red.** Write a failing test that names the behavior in `Given / When / Then`. Run it. *Confirm it fails for the right reason* — not a typo, not an import error. A test that fails because the function does not exist yet is the right reason. A test that fails because of a missing import is not.\\n2. **Green.** Write the minimum code to make the test pass. Resist adding the second case until the first passes. The second case is the next red.\\n3. **Refactor.** With the test green, restructure ruthlessly. The test is your safety net. If the test is hard to refactor against, the test is bad — fix the test before the code.\\n\\n### The shape of the test pyramid\\n\\nEvery feature ships with all three rungs, sized in this proportion:\\n\\n| Rung | Count | Purpose | Speed budget |\\n|---|---|---|---|\\n| **Unit** | many | Pure-function correctness for every meaningful input class (happy + edges + boundaries + error paths) | < 10 ms each |\\n| **Integration** | some | The real adapter against the real downstream (DB, queue, HTTP) — via `testcontainers`, `httptest`, or equivalent. NEVER a unit test pretending to be integration. | < 1 s each |\\n| **E2E scenario** | few | One narrative per user-visible outcome. Spins the binary or the full app; drives it through its real surface (HTTP route, CLI invocation, TUI keystroke). Asserts the *observable outcome*, not internal state. | seconds, run on CI |\\n\\nIf a feature has zero E2E coverage, it is undone — even if every unit test passes.\\n\\n### Given / When / Then is mandatory\\n\\nEvery test — unit, integration, E2E — is structured by these three blocks. Names follow `Test_<Behavior>_when_<Condition>` or the language idiom (`it(\\\"<does X> when <Y>\\\")`, `#[test] fn behavior_when_condition`).\\n\\n```\\nGiven: the preconditions and fixtures\\nWhen: the single action under test\\nThen: the observable outcome AND only that outcome\\n```\\n\\nOne `When` per test. Multiple `When`s = multiple tests. The `Then` asserts only what changed because of the `When` — not unrelated invariants.\\n\\n### Less mock, the better\\n\\nMocks are a last resort, not a default. The priority order:\\n\\n1. **Real object.** Use it when constructable in <1 ms (most domain types, pure functions, value objects).\\n2. **In-memory fake.** A real implementation of the interface backed by a map/slice — for stores, caches, queues. The fake has its OWN test that proves it behaves like the real one.\\n3. **Testcontainer / sandbox.** Real Postgres, real Redis, real S3-compatible (MinIO), via `testcontainers`. Slow but truthful.\\n4. **HTTP-level fake.** `httptest.Server` (Go), `respx` (Python), `msw` (TS) — fake at the wire, not at the SDK.\\n5. **Mock.** Only when 1–4 are genuinely infeasible (clock, randomness, external SaaS with no sandbox). Then mock the **narrowest** seam — never an entire service. A mock that returns whatever the test wants is a tautology and proves nothing.\\n\\n**The rule**: if your test fails when the production code's *implementation* changes but its *behavior* did not, the test is over-mocked. Delete the mock; assert on observable outputs.\\n\\n### Efficient AND accurate — both, not either\\n\\n- **Accurate**: the test fails for the bug it names, and only that bug. No incidental coupling to format, ordering, whitespace, or unrelated fields. Assert on the *contract*, not on the dump.\\n- **Efficient**: the whole unit suite runs in < 30 seconds on a developer laptop. The whole integration suite in < 5 minutes. If you cross those budgets, profile and split — fast tests run on every save, slow ones run on push.\\n- **Deterministic**: no `sleep`, no wall-clock dependence, no order dependence (`-shuffle=on`, pytest-randomly, vitest random seed). Inject a `Clock`. Subscribe to the event, do not poll for it. Time-based flake is a bug, not a test issue.\\n- **Isolated**: every test starts from a known fixture and tears down. `t.TempDir()`, `t.Setenv()`, transactional rollback for DB tests. Two tests passing individually but failing together is a fixture leak — fix it immediately.\\n\\n### Prompt tests follow the same rule\\n\\nWhen tests cover LLM prompts or agent outputs, assert on **parsed structure, decisions, or rule data**, never on exact prompt strings. Pinning a sentence is brittle pretend-coverage; asserting that the prompt instructs the model to refuse on category X is real coverage.\\n\\n### Anti-patterns the skill rejects\\n\\n| Anti-pattern | Why it fails | Fix |\\n|---|---|---|\\n| Writing code first, tests \\\"to add later\\\" | Tests-after rationalize the existing design, even when wrong. | Red first. Always. |\\n| One mega-test asserting 12 things | First failure hides the next 11. | Split by `Then` clause — one assertion class per test. |\\n| Mocking every collaborator | Test passes regardless of real behavior. | Use a fake or the real thing. Mock only true unmockables. |\\n| `time.sleep(0.1)` to \\\"let it finish\\\" | Flake guaranteed. | Subscribe to the completion signal; bounded await. |\\n| Snapshot tests for everything | Locks formatting, not behavior. | Snapshots for *structure* (CLI help, JSON shape). Assertions for *behavior*. |\\n| Removing a failing test to \\\"unblock CI\\\" | You just deleted a bug report. | Fix the code or fix the test — never delete to silence. |\\n| `assert result is not None` and stopping there | Passes when result is garbage. | Assert the *value*, not its existence. |\\n| Single happy-path E2E, no edges | Most bugs live on edges. | Edges are unit-test territory — but include at least one E2E that exercises an error path. |\\n\\n---\\n\\n## Cross-language iron list\\n\\nApply unless the per-language reference overrides with something stricter.\\n\\n| Rule | Python | Rust | TypeScript | Go |\\n|---|---|---|---|---|\\n| Immutable by default | `@dataclass(frozen=True, slots=True)` / Pydantic `frozen=True` | every binding is `let` (not `let mut`) unless mutation is the documented purpose | every field is `readonly`; arrays are `readonly T[]` | value types, unexported fields, no mutation methods unless mutation is the purpose |\\n| Branded primitives | `UserId = NewType(\\\"Use…2842 tokens truncated…ng.md) BEFORE the change** whenever your edit adds or modifies log lines, sets up a logger or a new service entrypoint, or handles errors at a boundary.\\n\\n---\\n\\n## MANDATORY POST-WRITE REVIEW LOOP\\n\\n**This runs EVERY time you finish writing or substantively editing code, before you claim the task is done.** No exceptions.\\n\\n### Step 1 — measure\\n\\nFor every file you created or modified:\\n\\n```bash\\nawk '!/^[[:space:]]*$/ && !/^[[:space:]]*(\\\\/\\\\/|#|--)/' <file> | wc -l\\n```\\n\\nOr run the per-language checker the skill ships:\\n\\n```bash\\n# Python\\nuv run scripts/python/check-no-excuse-rules.py <changed paths>\\n# Rust\\nbash scripts/rust/check-no-excuse-rules.sh <changed paths>\\n# TypeScript\\nbun run scripts/typescript/check-no-excuse-rules.ts <changed paths>\\n```\\n\\n### Step 2 — interpret\\n\\n| Pure LOC | Verdict | Required action |\\n|---|---|---|\\n| ≤ 200 | Healthy | continue |\\n| 200 - 250 | **Warning band** | State that fact and propose a split if the next edit will add lines. |\\n| > 250 | **DEFECT** | Do NOT commit new lines to this file. Refactor now: split the touched unit before adding lines, except for rare SIZE_OK or pure-data-table exceptions. |\\n\\n### Step 3 — architectural self-review (always, even at 80 LOC)\\n\\nAfter every code-writing session, answer these out loud (in your reply) before declaring done:\\n\\n1. **Single responsibility?** Can I name what this file owns in one short noun phrase? If the answer needs the word \\\"and\\\", split.\\n2. **Boundary purity?** Did I parse untrusted input into a typed value at the boundary, or did I pass `dict[str, Any]` / `serde_json::Value` / `unknown` past the boundary? If the latter, fix it.\\n3. **Variant discrimination?** Did I use `if`/`elif`/`else` (or `switch` without `assertNever`, or `match` without `assert_never`) anywhere to discriminate on a tagged type or enum? If yes, rewrite as exhaustive match.\\n4. **Escape hatches?** Any `Any`, `# type: ignore`, `unwrap`, `expect` outside `main`/tests, `as` numeric cast, `!`, `@ts-ignore`, `@ts-expect-error`, `#[allow]` on a real warning? If yes, fix the type or document why with a comment.\\n5. **Defensive layer?** Any null check, try/except, or `isinstance` guarding a value the type system already proves? If yes, delete.\\n6. **Helpers for one-off?** Any function, class, or trait introduced for a single caller that will never get a second caller? If yes, inline — axiom 0 should have caught it pre-write; this is the backstop.\\n7. **Tests?** Is the behavior I just introduced locked by a test that would fail if I revert this commit?\\n8. **Parameter bloat?** Any function I wrote or modified that takes more than 3 parameters — or smuggles them through a dict/kwargs/`...args`/throwaway options object? If yes, group related params into a typed value object. See [Smell 2](references/code-smells.md#smell-2--function-with-more-than-3-parameters).\\n9. **Redundant verification?** Did I perform a destructive action (delete, remove, clear) and then immediately re-query to \\\"confirm\\\" it worked? Did I call a setter then a getter to \\\"verify\\\"? If yes, delete the verification — the operation's contract IS the proof. See [Smell 3](references/code-smells.md#smell-3--redundant-verification-after-a-destructive-action).\\n10. **Negative naming?** Any variable, function, or flag named by the absence of a quality (`isNotValid`, `noErrors`, `DisableX`) when a positive name (`isValid`, `isClean`, `EnableX`) would work? If yes, rename to positive form and invert the branch. See [Smell 4](references/code-smells.md#smell-4--negative-form-names-and-conditions).\\n11. **Logging?** If I touched log lines, logger setup, or error boundaries: did I follow the project's existing practice (including its absence)? Is every new line leveled by its consumer, placed at a decision point, and message-stable with data in fields? See [`references/logging.md`](references/logging.md).\\n\\n**If any answer fails, fix it before declaring done.** This loop is the difference between \\\"the code compiles\\\" and \\\"the code is correct.\\\"\\n\\n### Step 4 — if you need to refactor right now, invoke the right skill\\n\\n- Any code smell from the [CODE SMELLS section](#code-smells--automatic-review-triggers) fired (250+ LOC, >3 params, redundant verification, negative naming), or step 3 surfaced more than two issues: **load the `refactor` skill** and execute its safe-refactor protocol (codemap, plan, LSP-driven edits, test after each step). Do not improvise a refactor under time pressure — the refactor skill exists precisely so you do not corrupt behavior while reshaping structure.\\n- You inherited a branch with AI-generated patterns (broad `except`, redundant null checks, vague TODOs, oversized modules, dead helpers, redundant post-action verification): **load the `remove-ai-slops` skill** to do a categorized branch-scope cleanup with regression tests pinned first.\\n\\nThese two skills are not optional cosmetics. They are the recovery path for the smells this loop is designed to catch.\\n\\n---\\n\\n## Companion skills - explicit invocation triggers\\n\\n| Trigger | Skill to load | Why |\\n|---|---|---|\\n| Any [code smell](#code-smells--automatic-review-triggers) fires (250+ LOC, >3 params, redundant verification), OR the post-write loop surfaces 2+ issues, OR the user says \\\"reshape this\\\", \\\"extract this\\\", \\\"clean this up\\\" | `refactor` | Safe codemap-driven multi-step refactor with LSP + tests after each step. Never improvise a structural change. |\\n| Recent branch contains AI-authored patterns (broad except, dead helpers, vague comments, oversized files, redundant post-action verification), OR the user says \\\"remove slop\\\", \\\"clean AI code\\\", \\\"deslop\\\" | `remove-ai-slops` | Tests pinned FIRST, then categorized parallel cleanup, then quality gates. Behavior-preserving. |\\n| Rust code touches `unsafe`, `*mut`, `*const`, `MaybeUninit`, FFI, `unsafe impl Send/Sync`, or a custom lock-free primitive | `references/rust-ub/` | Full UB taxonomy + Miri strictness escalation. Every `unsafe` block must survive Miri Level 3 (strict provenance + symbolic alignment + preemption) before it ships. |\\n\\n---\\n\\n## Per-language jump table\\n\\n**Stop. Read the matching reference fully before writing code.**\\n\\n### Python (`.py`, `.pyi`)\\n\\n**READ `references/python/README.md` FIRST.** Then load on demand:\\n\\n| Need | Load |\\n|---|---|\\n| Strict pyproject.toml / basedpyright / ruff config | `references/python/pyproject-strict.md` |\\n| Type patterns (`NewType`, `Final`, `TypeGuard`, `Protocol`) | `references/python/type-patterns.md` |\\n| Data modeling (Pydantic vs dataclass vs TypedDict vs StrEnum) | `references/python/data-modeling.md` |\\n| Error handling (typed exceptions, exhaustive match, union returns) | `references/python/error-handling.md` |\\n| Async with anyio (task groups, cancel scopes, channels) | `references/python/async-anyio.md` |\\n| httpx2 production defaults (HTTP/2, brotli+zstd, pool tuning) | `references/python/httpx2-optimization.md` |\\n| **orjson** in hot paths (FastAPI integration, Pydantic v2 `model_dump_json` vs orjson, Redis/queue/log) | `references/python/orjson-stack.md` |\\n| Data processing with polars + duckdb (NEVER pandas) | `references/python/data-processing.md` |\\n| FastAPI + SQLAlchemy 2.x async stack | `references/python/fastapi-stack.md` |\\n| pydantic-ai agents | `references/python/pydantic-ai.md` |\\n| Textual TUI | `references/python/textual-tui.md` |\\n| Disposable PEP 723 scripts | `references/python/one-liners.md` |\\n| Canonical library defaults | `references/python/libraries.md` |\\n\\n### Rust (`.rs`, `Cargo.toml`)\\n\\n**READ `references/rust/README.md` FIRST.** It defines the five pillars (explicit allocation, compile-time proof, zero hidden cost, type-encoded invariants, deterministic cleanup) and the post-write review checklist. Then load on demand:\\n\\n| Need | Load |\\n|---|---|\\n| **Arena allocation, const fn, zero-alloc APIs, bitfield, scopeguard, errdefer, Zig-like patterns** | **`references/rust/zero-cost-safety.md`** |\\n| Strict `Cargo.toml` lints + profile + workspace config | `references/rust/cargo-strict.md` |\\n| Type-state and newtype patterns (Chris Allen's `Point<Screen>` rule) | `references/rust/type-state.md` |\\n| `unsafe` discipline (safe wrapper + SAFETY comment + miri proof) | `references/rust/unsafe-discipline.md` |\\n| Async with tokio (JoinSet, cancellation, select, blocking work) | `references/rust/async-tokio.md` |\\n| Concurrency primitives (locks, atomics, channels, loom) | `references/rust/concurrency.md` |\\n| axum + sqlx + tracing + tower HTTP stack | `references/rust/axum-stack.md` |\\n| clap + color-eyre + tracing + indicatif CLI stack | `references/rust/clap-stack.md` |\\n| Property tests (proptest) + snapshot tests (insta) | `references/rust/proptest-insta.md` |\\n| Disposable `rust-script` scripts | `references/rust/one-liners.md` |\\n| Canonical library defaults | `references/rust/libraries.md` |\\n| **ANY `unsafe` / FFI / `MaybeUninit` / lock-free work** | **`references/rust-ub/` (full directory)** |\\n\\n### TypeScript (`.ts`, `.tsx`, `.mts`, `.cts`)\\n\\n**READ `references/typescript/README.md` FIRST.** Then load on demand:\\n\\n| Need | Load |\\n|---|---|\\n| Strict tsconfig + Biome config | `references/typescript/tsconfig-strict.md` |\\n| Type patterns (branded types, `as const`, `satisfies`, narrowing, `assertNever`) | `references/typescript/type-patterns.md` |\\n| Data modeling (type vs interface vs Zod, readonly, parse-don't-validate) | `references/typescript/data-modeling.md` |\\n| Error handling (Result, typed errors, union vs throw, AbortSignal timeouts) | `references/typescript/error-handling.md` |\\n| Bootstrapping a new project (Bun, pnpm, Hono, Vite) | `references/typescript/bootstrap.md` |\\n| Hono backend stack (hono-openapi, Scalar, Swagger, Zod v4) | `references/typescript/backend-hono.md` |\\n\\n### Go (`.go`, `go.mod`, `go.sum`, `.golangci.yml`, `*.proto`)\\n\\n**READ `references/go/README.md` FIRST.** Then load on demand:\\n\\n| Need | Load |\\n|---|---|\\n| Library defaults (gin vs chi, sqlc, slog, the 2026 stack reasoning) | `references/go/libraries.md` |\\n| Canonical strict `.golangci.yml` (v2) with per-linter rationale | `references/go/golangci-strict.md` |\\n| Project layout, Taskfile, CI, `go.mod` template | `references/go/bootstrap.md` |\\n| Type patterns (named types, smart constructors, sealed interfaces, generics) | `references/go/type-patterns.md` |\\n| Data modeling — the three layers of validation (validator/v10 → smart ctor → sqlc) | `references/go/data-modeling.md` |\\n| Error handling (`errors.Is/As`, typed errors, `%w` wrapping, no panic) | `references/go/error-handling.md` |\\n| Concurrency (`context.Context`, `errgroup`, channels, locks, `-race`, `goleak`) | `references/go/concurrency.md` |\\n| HTTP backend stack (gin + slog + validator + pgx, middleware ordering, SSE, WS) | `references/go/backend-stack.md` |\\n| RPC stack (Connect-Go default, grpc-go fallback, protovalidate, Buf) | `references/go/grpc-connect.md` |\\n| CLI stack (cobra + slog + huh) | `references/go/cobra-stack.md` |\\n| Database stack (sqlc + pgx + goose + testcontainers) | `references/go/sqlc-pgx.md` |\\n| TUI stack (bubbletea v2 + bubbles v2 + lipgloss v2; **CJK / IME support**) | `references/go/bubbletea-v2.md` |\\n| Testing (Given/When/Then, table-driven, fakes-over-mocks, autogold, rapid) | `references/go/testing.md` |\\n| Disposable `go run` scripts | `references/go/one-liners.md` |\\n\\n---\\n\\n## Activation\\n\\nThis skill activates whenever you are writing or modifying any `.py`, `.pyi`, `.rs`, `.ts`, `.tsx`, `.mts`, `.cts`, `.go` file, or any project manifest (`pyproject.toml`, `Cargo.toml`, `package.json`, `tsconfig.json`, `biome.json`, `go.mod`, `go.sum`, `.golangci.yml`, `Taskfile.yml`, `buf.yaml`, `sqlc.yaml`). **Even one-off scripts get the full treatment** - that is the whole point of `uv run` + PEP 723, `rust-script`, `bun run`, and `go run` + `//go:build ignore`: production hygiene with throwaway ergonomics.\\n\\nThe references contain the recipes. **Read them before writing code. Re-read them when the model drifts.** The post-write review loop is non-negotiable.\\n\"}}"}],"internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012323.6554484}}}
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{"timestamp":"2026-09-10T03:52:14.913Z","ordinal":36,"type":"event_msg","payload":{"type":"item_completed","thread_id":"01a08971-6519-7cf3-9399-e7f6b9686fbc","turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","item":{"type":"CommandExecution","id":"exec-072e5b26-5eb4-4ef5-af3b-adbee0aebf67","process_id":"47164","command":["/usr/bin/bash","-lc","cat /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/sisyphuslabs/omo/4.16.1/skills/programming/references/python/README.md"],"cwd":"file:///lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/kitchen","parsed_cmd":[{"type":"read","cmd":"cat /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/sisyphuslabs/omo/4.16.1/skills/programming/references/python/README.md","name":"README.md","path":"/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/sisyphuslabs/omo/4.16.1/skills/programming/references/python/README.md"}],"source":"unified_exec_startup","status":"completed","stdout":"\n# Python Programmer\n\nModern Python. Type-strict, stack-first, async-correct.\n\n## Philosophy\n\nThe type checker is your compiler. Make illegal states unrepresentable. Parse at boundaries. Own resources explicitly. Every function has a contract; the type system enforces it.\n\n## Hard rules\n\nThese are deliberate project choices. Violations are always wrong, not \"style preferences\".\n\n### Tooling\n\n| Category | Use | Never |\n|---|---|---|\n| Package manager | `uv` | pip, poetry, conda, pipenv |\n| Type checker | `basedpyright` (`typeCheckingMode = \"all\"`) | pyright, mypy |\n| Linter + formatter | `ruff` (`select = [\"ALL\"]`) | flake8, black, isort, autopep8 |\n| Async runtime | `anyio` | `import asyncio` |\n| Data | `polars` + `duckdb` + `numpy` | pandas |\n| Web framework | FastAPI + Pydantic v2 | Flask, Django REST |\n| ORM | SQLAlchemy 2.x async | Django ORM, Tortoise |\n| HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) | requests, aiohttp, httpx |\n| Testing | `pytest` | unittest |\n| CLI | `typer` + `rich` | argparse, click, fire |\n\n### The iron list\n\n1. **Frozen by default** — `@dataclass(frozen=True, slots=True)`. Pydantic: `model_config = ConfigDict(frozen=True)`. Mutable only when mutation is the documented purpose.\n2. **NewType for distinct IDs** — `UserId = NewType(\"UserId\", int)`. Never pass raw `int` where a branded type exists.\n3. **`match` only for variants, `if` only for booleans** — **NEVER** use `if/elif/else` to discriminate on type (`isinstance`), enum value, or literal variant. `match/case` is mandatory for these — non-negotiable. **ALWAYS** end with `case unreachable: assert_never(unreachable)` — bare `case _: pass` and `case _: raise ValueError` are banned (they silently swallow new variants). `if/else` is fine only for boolean expressions, range checks, and predicate calls that aren't variant discrimination. See \"Why `if/elif` on variants is banned\" below for examples.\n4. **Protocol over ABC** — `typing.Protocol` for interfaces. ABC only when you need shared method implementation.\n5. **No raw dicts in signatures** — params and returns use `TypedDict`, `dataclass`, or Pydantic model. Internal scratch dicts are fine.\n6. **Parse, don't validate** — constructors produce typed objects or raise. Never pass unvalidated data deeper into the call stack.\n7. **Typed errors** — error types are dataclasses or exceptions with typed fields. Never `raise ValueError(\"something\")` with a bare string. Use union returns when the caller is within 1-2 call levels and must handle the outcome (repository → service). Use exceptions when the error should propagate up many layers to a boundary handler (service → HTTP handler).\n8. **Final for constants** — module-level constants use `Final`. Mutable module globals are a code smell.\n9. **Explicit None** — annotate `-> X | None`. Never return `None` from a function whose signature omits it.\n10. **Context managers for resources** — files, DB connections, HTTP clients, locks. No manual `.close()`.\n11. **No Any, no object** — both are banned as type annotations. `object` erases all structural information (zero callable attributes, zero narrowing). Use `Protocol` (structural typing), `TypeVar` (generic pass-through), explicit union (known variants), or `TypedDict` (dict shapes).\n12. **No cast** — `cast()` is banned. Redesign the types.\n13. **No type: ignore** — fix the type error. The checker is right; you are wrong.\n14. **No broad except** — `except Exception` and `except BaseException` are banned. Catch the **specific** exception you expect. A broad catch swallows bugs you need to see — `KeyError`, `AttributeError`, `TypeError` all vanish silently. If you genuinely need a catch-all at a top-level boundary (CLI entry, HTTP handler), use `# noqa: BROAD_EXCEPT_OK` and log + re-raise.\n\n### Typing and safety\n\n- `basedpyright` in `typeCheckingMode = \"all\"`. Every public function has full annotations. Internal helpers: annotate return type; parameter types may be inferred.\n- `ruff` with `select = [\"ALL\"]`. Override specific rules per project in `pyproject.toml`, never globally disable the strict baseline.\n- Every new function must have a `docstring` unless its name + signature makes it completely obvious (e.g. `def full_name(first: str, last: str) -> str:`).\n- Use `X | Y` union syntax (PEP 604), never `Union[X, Y]` or `Optional[X]`.\n\n### Why `object` is banned\n\n`object` pretends to be safe (\"it's the top type!\") but gives **zero** narrowing and **zero** attributes. Even `Any` is more honest — it admits the boundary is untyped.\n\n```python\n# BANNED\ndef process(data: object) -> object: ...\ndef store(items: list[object]) -> None: ...\nresults: dict[str, object] = {}\n\n# GOOD — Protocol for structural typing\nclass Serializable(Protocol):\n def serialize(self) -> bytes: ...\ndef process(data: Serializable) -> ProcessResult: ...\n\n# GOOD — TypeVar for generic pass-through\ndef identity[T](x: T) -> T: ...\ndef first[T](items: Sequence[T]) -> T: ...\n\n# GOOD — explicit union for known variants\ndef parse(raw: str | bytes) -> Document: ...\n```\n\n### Why `if/elif` on variants is banned\n\n`if/elif/else` chains on type, enum, or literal values lose compile-time exhaustiveness. When a new variant is added, nothing warns you. `match/case` + `assert_never` does.\n\n```python\n# BANNED — if/elif for type discrimination\nif isinstance(event, Click):\n handle_click(event.x, event.y)\nelif isinstance(event, Scroll):\n handle_scroll(event.delta)\nelse:\n raise ValueError(f\"Unknown: {event}\") # runtime bomb\n\n# BANNED — if/elif for enum discrimination\nif status == Status.PENDING:\n start_review()\nelif status == Status.ACTIVE:\n continue_processing()\nelif status == Status.CLOSED:\n archive()\n\n# BANNED — non-exhaustive match (swallows new variants)\nmatch event:\n case Click(x, y): handle_click(x, y)\n case _: pass\n\n# GOOD — exhaustive match with assert_never\nmatch event:\n case Click(x=x, y=y):\n handle_click(x, y)\n case Scroll(delta=delta):\n handle_scroll(delta)\n case unreachable:\n assert_never(unreachable)\n\n# GOOD — enum match\nmatch status:\n case Status.PENDING: start_review()\n case Status.ACTIVE: continue_processing()\n case Status.CLOSED: archive()\n case unreachable: assert_never(unreachable)\n```\n\n`if/else` is fine for boolean conditions and range checks — things that aren't variant discrimination:\n\n```python\n# FINE — boolean, not variant\nif age >= 18:\n grant_access()\nelse:\n deny_access()\n```\n\n### Why broad `except` is banned\n\n`except Exception` catches **every** non-system exception — `KeyError`, `TypeError`, `AttributeError`, `ValueError` all vanish. You lose the stack trace that would have told you exactly what went wrong. The fix is always to name the exception you expect.\n\n```python\n# BANNED — swallows bugs\ntry:\n result = api.fetch(url)\nexcept Exception as e:\n logger.error(e)\n return None\n\n# BANNED — catch-and-ignore\ntry:\n parse(data)\nexcept Exception:\n pass\n\n# GOOD — catch what you expect\ntry:\n result = api.fetch(url)\nexcept httpx.HTTPStatusError as e:\n logger.error(\"API %d: %s\", e.response.status_code, e.request.url)\n return None\nexcept httpx.ConnectError:\n raise ServiceUnavailableError(service=\"api\") from None\n\n# GOOD — top-level boundary (only place broad catch is acceptable)\ndef main() -> int: # noqa: BROAD_EXCEPT_OK\n try:\n return run()\n except Exception:\n logger.exception(\"unhandled error\")\n return 1\n```\n\n### Async\n\n- `import asyncio` is **BANNED**. Use `import anyio`.\n- For background tasks, use `anyio.create_task_group`. Never fire-and-forget with `asyncio.create_task`.\n- For concurrency gates, use `anyio.CapacityLimiter` (not `asyncio.Semaphore`).\n- Load `async-anyio.md` when writing async code for the full pattern library.\n\n### Data modeling — which container, when\n\nAll model fields carry type annotations. No `Any`, no untyped dicts in public APIs.\nUse `polars` + `duckdb` for data. pandas is never the right answer in this stack.\n\n| Situation | Use |\n|---|---|\n| User input, API request/response | `Pydantic BaseModel (frozen=True)` |\n| Internal value object (no I/O) | `@dataclass(frozen=True, slots=True)` |\n| Function with multiple outcomes | Union of frozen dataclasses + `match` |\n| Dict shape for JSON compat / `**kwargs` | `TypedDict` |\n| Fixed constants | `StrEnum` / `IntEnum` |\n| Distinct primitive (UserId vs MovieId) | `NewType` |\n| Contract / capability | `Protocol` |\n| Contract + shared implementation | `ABC` |\n| ORM model (SQLAlchemy) | `Mapped[]` — inherently mutable, `# noqa: MUTABLE_OK` |\n| Config from env vars | `pydantic-settings BaseSettings` |\n\n**The one rule**: data crosses trust boundary → Pydantic. Everything else → dataclass.\n\nLoad `data-modeling.md` for the full decision flowchart and comparison matrix.\n\n### When frozen=True does not apply\n\n- **ORM models** — SQLAlchemy `Mapped[]` requires mutation. Use `# noqa: MUTABLE_OK`.\n- **Builder / accumulator** — object exists to be mutated (counter, buffer, state machine). Docstring must explain why.\n- **Pydantic Settings** — tests override fields. Mutable is acceptable.\n\nIf you need `# noqa: MUTABLE_OK`, the class docstring must say why mutation is required.\n\n### Libraries\n\nCanonical defaults (override only if `pyproject.toml` explicitly picks something else):\n\n| Domain | Library | Reason |\n|---|---|---|\n| CLI | `typer` | Type-annotated CLI from function sigs |\n| Pretty output | `rich` | Tables, progress, tracebacks, markdown |\n| HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) | Next-gen HTTP client (Pydantic stewardship), HTTP/2, brotli+zstd. Always `httpx2[http2,brotli,zstd]`. See `httpx2-optimization.md` |\n| Validation | `pydantic` v2 | Fast native validator, JSON Schema |\n| Web API | `fastapi` | Async, Pydantic-native, OpenAPI |\n| ORM | `sqlalchemy` 2.x async | `Mapped[]` types, async sessions |\n| DB driver (Postgres) | `asyncpg` (via SQLAlchemy) | Fastest PG driver |\n| AI agents | `pydantic-ai` | Typed deps, structured output |\n| TUI | `textual` | Rich-based, CSS layout, widgets |\n| Logging | `rich.logging.RichHandler` | Pretty; swap to `structlog` in prod |\n\n## pyproject.toml — the one true config\n\nScaffold a new project with all strict defaults pre-configured:\n\n```bash\nuv run ../../scripts/python/new-project.py myproject\nuv run ../../scripts/python/new-project.py myproject --path ./workspace\nuv run ../../scripts/python/new-project.py myproject --lib # publishable library\n```\n\nCreates via `uv init`, then injects basedpyright `typeCheckingMode = \"all\"` + ruff `select = [\"ALL\"]` + pytest strict. Cross-platform (macOS, Linux, Windows).\n\nFor manual setup: `uv init --app myproject`, then load `pyproject-strict.md`.\n\n## PEP 723 — inline script metadata (mandatory for ALL scripts)\n\nEvery `.py` script — even throwaway — MUST use PEP 723 inline metadata with the `# ─── How to run ───` comment block. No venv, no `requirements.txt`. The script IS the environment spec. A script without the usage comment block is incomplete.\n\nScaffold with: `uv run ../../scripts/python/new-script.py <name> --deps \"httpx2[http2,brotli,zstd]\"` (writes to temp dir by default, `--output` for specific path).\n\nLoad `one-liners.md` for full patterns, examples, and anti-patterns.\n\n## Reference loading\n\nLoad on demand — not all at once.\n\n| Need | Load |\n|---|---|\n| Full pyproject.toml config | `pyproject-strict.md` |\n| Type patterns (NewType, Final, enums, narrowing) | `type-patterns.md` |\n| Data modeling (container choice, frozen, parse-don't-validate) | `data-modeling.md` |\n| Error handling (typed errors, union returns, exhaustive match) | `error-handling.md` |\n| Async patterns (anyio) | `async-anyio.md` |\n| Data processing (polars / duckdb) | `data-processing.md` |\n| FastAPI + SQLAlchemy stack | `fastapi-stack.md` |\n| Library decision tree | `libraries.md` |\n| **httpx2 optimization** (MUST load for any network code) | `httpx2-optimization.md` |\n| **orjson** (when JSON is in the hot path; FastAPI/Pydantic v2 integration) | `orjson-stack.md` |\n| One-liner scripts (PEP 723) | `one-liners.md` |\n| PydanticAI agents | `pydantic-ai.md` |\n| Textual TUI | `textual-tui.md` |\n\n## httpx2 — mandatory for ALL network requests\n\nEvery outgoing HTTP call MUST use [`httpx2`](https://github.com/pydantic/httpx2) (`httpx2[http2,brotli,zstd]`). Never `requests`, never `aiohttp`, never the original `httpx`.\n\n**ALL optimizations are ON by default — not optional, not progressive, not \"nice to have\".** A bare `httpx2.AsyncClient()` is a bug — treat it like a lint violation. The correct way is the factory pattern in `httpx2-optimization.md` with: HTTP/2 enabled, tuned connection pool (200/40/30s), split timeouts (5/30/10/10), transport retries (3), TCP_NODELAY, follow_redirects, and event hooks for observability.\n\nWhen writing or reviewing ANY network code, **ALWAYS load `httpx2-optimization.md`** and use the factory pattern verbatim. No exceptions.\n\n## No-excuse audit\n\nViolations caught by `../../scripts/python/check-no-excuse-rules.py`. Run after every edit session.\n\n| Rule ID | Catches | Opt-out |\n|---|---|---|\n| `cast-any` | `cast(Any, ...)` | None — redesign types |\n| `type-ignore` | `# type: ignore` | None — fix the type |\n| `pyright-ignore` | `# pyright: ignore` | None — fix the type |\n| `bare-except` | `except:` with no class | None — name the exception |\n| `silent-except` | `except X: pass` / `except X: ...` | None — handle or re-raise |\n| `no-asyncio` | `import asyncio` | `# noqa: ANYIO_OK` |\n| `no-pandas` | `import pandas` | `# noqa: PANDAS_OK` |\n| `mutable-dataclass` | `@dataclass` without `frozen=True` | `# noqa: MUTABLE_OK` |\n| `missing-slots` | `@dataclass` without `slots=True` | `# noqa: SLOTS_OK` |\n| `raw-dict-return` | `-> dict` in function return type | `# noqa: DICT_OK` |\n| `missing-assert-never` | `match` block without `assert_never` default | `# noqa: MATCH_OK` |\n| `generic-exception` | `raise ValueError(\"...\")` / `raise TypeError(\"...\")` with bare string | `# noqa: GENERIC_ERR_OK` |\n| `no-object` | `object` used as type annotation (param, return, generic arg) | `# noqa: OBJECT_OK` |\n| `if-elif-on-variant` | `if isinstance()`/`if x == Enum.V` chain that should be `match/case` | `# noqa: IF_VARIANT_OK` |\n| `oversized-module` | File exceeds 250 pure LOC (non-blank, non-comment) | `# noqa: SIZE_OK` |\n| `broad-except` | `except Exception` / `except BaseException` (too broad) | `# noqa: BROAD_EXCEPT_OK` |\n\nFix every violation before declaring work done. basedpyright + ruff strict config catches the rest.\n\n## In tests\n\nTests are strict too, with these exceptions (already configured in `pyproject.toml` per-file-ignores):\n\n| In tests you may | Why |\n|---|---|\n| Use `assert` | That's how pytest works (`S101` ignored) |\n| Use magic numbers | Test data (`PLR2004` ignored) |\n| Access `_private` members | Testing internals (`SLF001` ignored) |\n| Skip docstrings | Test names are the docs (`D` ignored) |\n| Have unused function args | Fixtures (`ARG` ignored) |\n\nTests still follow the iron list — frozen dataclasses, typed errors, exhaustive match. If test fixtures need mutable state, use `# noqa: MUTABLE_OK` on the fixture class.\n\n## Existing codebases\n\nWhen editing an existing file that doesn't follow these rules: **write new code in strict style, don't refactor existing code in the same change.** Mixing feature work with style migration makes reviews harder and bugs likelier.\n\n## Activation\n\nThis skill activates whenever you are writing or modifying any `.py` file. Even one-off scripts get the strict treatment — that is the whole point of PEP 723 + uv: production hygiene with throwaway ergonomics.\n","stderr":"","aggregated_output":"\n# Python Programmer\n\nModern Python. Type-strict, stack-first, async-correct.\n\n## Philosophy\n\nThe type checker is your compiler. Make illegal states unrepresentable. Parse at boundaries. Own resources explicitly. Every function has a contract; the type system enforces it.\n\n## Hard rules\n\nThese are deliberate project choices. Violations are always wrong, not \"style preferences\".\n\n### Tooling\n\n| Category | Use | Never |\n|---|---|---|\n| Package manager | `uv` | pip, poetry, conda, pipenv |\n| Type checker | `basedpyright` (`typeCheckingMode = \"all\"`) | pyright, mypy |\n| Linter + formatter | `ruff` (`select = [\"ALL\"]`) | flake8, black, isort, autopep8 |\n| Async runtime | `anyio` | `import asyncio` |\n| Data | `polars` + `duckdb` + `numpy` | pandas |\n| Web framework | FastAPI + Pydantic v2 | Flask, Django REST |\n| ORM | SQLAlchemy 2.x async | Django ORM, Tortoise |\n| HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) | requests, aiohttp, httpx |\n| Testing | `pytest` | unittest |\n| CLI | `typer` + `rich` | argparse, click, fire |\n\n### The iron list\n\n1. **Frozen by default** — `@dataclass(frozen=True, slots=True)`. Pydantic: `model_config = ConfigDict(frozen=True)`. Mutable only when mutation is the documented purpose.\n2. **NewType for distinct IDs** — `UserId = NewType(\"UserId\", int)`. Never pass raw `int` where a branded type exists.\n3. **`match` only for variants, `if` only for booleans** — **NEVER** use `if/elif/else` to discriminate on type (`isinstance`), enum value, or literal variant. `match/case` is mandatory for these — non-negotiable. **ALWAYS** end with `case unreachable: assert_never(unreachable)` — bare `case _: pass` and `case _: raise ValueError` are banned (they silently swallow new variants). `if/else` is fine only for boolean expressions, range checks, and predicate calls that aren't variant discrimination. See \"Why `if/elif` on variants is banned\" below for examples.\n4. **Protocol over ABC** — `typing.Protocol` for interfaces. ABC only when you need shared method implementation.\n5. **No raw dicts in signatures** — params and returns use `TypedDict`, `dataclass`, or Pydantic model. Internal scratch dicts are fine.\n6. **Parse, don't validate** — constructors produce typed objects or raise. Never pass unvalidated data deeper into the call stack.\n7. **Typed errors** — error types are dataclasses or exceptions with typed fields. Never `raise ValueError(\"something\")` with a bare string. Use union returns when the caller is within 1-2 call levels and must handle the outcome (repository → service). Use exceptions when the error should propagate up many layers to a boundary handler (service → HTTP handler).\n8. **Final for constants** — module-level constants use `Final`. Mutable module globals are a code smell.\n9. **Explicit None** — annotate `-> X | None`. Never return `None` from a function whose signature omits it.\n10. **Context managers for resources** — files, DB connections, HTTP clients, locks. No manual `.close()`.\n11. **No Any, no object** — both are banned as type annotations. `object` erases all structural information (zero callable attributes, zero narrowing). Use `Protocol` (structural typing), `TypeVar` (generic pass-through), explicit union (known variants), or `TypedDict` (dict shapes).\n12. **No cast** — `cast()` is banned. Redesign the types.\n13. **No type: ignore** — fix the type error. The checker is right; you are wrong.\n14. **No broad except** — `except Exception` and `except BaseException` are banned. Catch the **specific** exception you expect. A broad catch swallows bugs you need to see — `KeyError`, `AttributeError`, `TypeError` all vanish silently. If you genuinely need a catch-all at a top-level boundary (CLI entry, HTTP handler), use `# noqa: BROAD_EXCEPT_OK` and log + re-raise.\n\n### Typing and safety\n\n- `basedpyright` in `typeCheckingMode = \"all\"`. Every public function has full annotations. Internal helpers: annotate return type; parameter types may be inferred.\n- `ruff` with `select = [\"ALL\"]`. Override specific rules per project in `pyproject.toml`, never globally disable the strict baseline.\n- Every new function must have a `docstring` unless its name + signature makes it completely obvious (e.g. `def full_name(first: str, last: str) -> str:`).\n- Use `X | Y` union syntax (PEP 604), never `Union[X, Y]` or `Optional[X]`.\n\n### Why `object` is banned\n\n`object` pretends to be safe (\"it's the top type!\") but gives **zero** narrowing and **zero** attributes. Even `Any` is more honest — it admits the boundary is untyped.\n\n```python\n# BANNED\ndef process(data: object) -> object: ...\ndef store(items: list[object]) -> None: ...\nresults: dict[str, object] = {}\n\n# GOOD — Protocol for structural typing\nclass Serializable(Protocol):\n def serialize(self) -> bytes: ...\ndef process(data: Serializable) -> ProcessResult: ...\n\n# GOOD — TypeVar for generic pass-through\ndef identity[T](x: T) -> T: ...\ndef first[T](items: Sequence[T]) -> T: ...\n\n# GOOD — explicit union for known variants\ndef parse(raw: str | bytes) -> Document: ...\n```\n\n### Why `if/elif` on variants is banned\n\n`if/elif/else` chains on type, enum, or literal values lose compile-time exhaustiveness. When a new variant is added, nothing warns you. `match/case` + `assert_never` does.\n\n```python\n# BANNED — if/elif for type discrimination\nif isinstance(event, Click):\n handle_click(event.x, event.y)\nelif isinstance(event, Scroll):\n handle_scroll(event.delta)\nelse:\n raise ValueError(f\"Unknown: {event}\") # runtime bomb\n\n# BANNED — if/elif for enum discrimination\nif status == Status.PENDING:\n start_review()\nelif status == Status.ACTIVE:\n continue_processing()\nelif status == Status.CLOSED:\n archive()\n\n# BANNED — non-exhaustive match (swallows new variants)\nmatch event:\n case Click(x, y): handle_click(x, y)\n case _: pass\n\n# GOOD — exhaustive match with assert_never\nmatch event:\n case Click(x=x, y=y):\n handle_click(x, y)\n case Scroll(delta=delta):\n handle_scroll(delta)\n case unreachable:\n assert_never(unreachable)\n\n# GOOD — enum match\nmatch status:\n case Status.PENDING: start_review()\n case Status.ACTIVE: continue_processing()\n case Status.CLOSED: archive()\n case unreachable: assert_never(unreachable)\n```\n\n`if/else` is fine for boolean conditions and range checks — things that aren't variant discrimination:\n\n```python\n# FINE — boolean, not variant\nif age >= 18:\n grant_access()\nelse:\n deny_access()\n```\n\n### Why broad `except` is banned\n\n`except Exception` catches **every** non-system exception — `KeyError`, `TypeError`, `AttributeError`, `ValueError` all vanish. You lose the stack trace that would have told you exactly what went wrong. The fix is always to name the exception you expect.\n\n```python\n# BANNED — swallows bugs\ntry:\n result = api.fetch(url)\nexcept Exception as e:\n logger.error(e)\n return None\n\n# BANNED — catch-and-ignore\ntry:\n parse(data)\nexcept Exception:\n pass\n\n# GOOD — catch what you expect\ntry:\n result = api.fetch(url)\nexcept httpx.HTTPStatusError as e:\n logger.error(\"API %d: %s\", e.response.status_code, e.request.url)\n return None\nexcept httpx.ConnectError:\n raise ServiceUnavailableError(service=\"api\") from None\n\n# GOOD — top-level boundary (only place broad catch is acceptable)\ndef main() -> int: # noqa: BROAD_EXCEPT_OK\n try:\n return run()\n except Exception:\n logger.exception(\"unhandled error\")\n return 1\n```\n\n### Async\n\n- `import asyncio` is **BANNED**. Use `import anyio`.\n- For background tasks, use `anyio.create_task_group`. Never fire-and-forget with `asyncio.create_task`.\n- For concurrency gates, use `anyio.CapacityLimiter` (not `asyncio.Semaphore`).\n- Load `async-anyio.md` when writing async code for the full pattern library.\n\n### Data modeling — which container, when\n\nAll model fields carry type annotations. No `Any`, no untyped dicts in public APIs.\nUse `polars` + `duckdb` for data. pandas is never the right answer in this stack.\n\n| Situation | Use |\n|---|---|\n| User input, API request/response | `Pydantic BaseModel (frozen=True)` |\n| Internal value object (no I/O) | `@dataclass(frozen=True, slots=True)` |\n| Function with multiple outcomes | Union of frozen dataclasses + `match` |\n| Dict shape for JSON compat / `**kwargs` | `TypedDict` |\n| Fixed constants | `StrEnum` / `IntEnum` |\n| Distinct primitive (UserId vs MovieId) | `NewType` |\n| Contract / capability | `Protocol` |\n| Contract + shared implementation | `ABC` |\n| ORM model (SQLAlchemy) | `Mapped[]` — inherently mutable, `# noqa: MUTABLE_OK` |\n| Config from env vars | `pydantic-settings BaseSettings` |\n\n**The one rule**: data crosses trust boundary → Pydantic. Everything else → dataclass.\n\nLoad `data-modeling.md` for the full decision flowchart and comparison matrix.\n\n### When frozen=True does not apply\n\n- **ORM models** — SQLAlchemy `Mapped[]` requires mutation. Use `# noqa: MUTABLE_OK`.\n- **Builder / accumulator** — object exists to be mutated (counter, buffer, state machine). Docstring must explain why.\n- **Pydantic Settings** — tests override fields. Mutable is acceptable.\n\nIf you need `# noqa: MUTABLE_OK`, the class docstring must say why mutation is required.\n\n### Libraries\n\nCanonical defaults (override only if `pyproject.toml` explicitly picks something else):\n\n| Domain | Library | Reason |\n|---|---|---|\n| CLI | `typer` | Type-annotated CLI from function sigs |\n| Pretty output | `rich` | Tables, progress, tracebacks, markdown |\n| HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) | Next-gen HTTP client (Pydantic stewardship), HTTP/2, brotli+zstd. Always `httpx2[http2,brotli,zstd]`. See `httpx2-optimization.md` |\n| Validation | `pydantic` v2 | Fast native validator, JSON Schema |\n| Web API | `fastapi` | Async, Pydantic-native, OpenAPI |\n| ORM | `sqlalchemy` 2.x async | `Mapped[]` types, async sessions |\n| DB driver (Postgres) | `asyncpg` (via SQLAlchemy) | Fastest PG driver |\n| AI agents | `pydantic-ai` | Typed deps, structured output |\n| TUI | `textual` | Rich-based, CSS layout, widgets |\n| Logging | `rich.logging.RichHandler` | Pretty; swap to `structlog` in prod |\n\n## pyproject.toml — the one true config\n\nScaffold a new project with all strict defaults pre-configured:\n\n```bash\nuv run ../../scripts/python/new-project.py myproject\nuv run ../../scripts/python/new-project.py myproject --path ./workspace\nuv run ../../scripts/python/new-project.py myproject --lib # publishable library\n```\n\nCreates via `uv init`, then injects basedpyright `typeCheckingMode = \"all\"` + ruff `select = [\"ALL\"]` + pytest strict. Cross-platform (macOS, Linux, Windows).\n\nFor manual setup: `uv init --app myproject`, then load `pyproject-strict.md`.\n\n## PEP 723 — inline script metadata (mandatory for ALL scripts)\n\nEvery `.py` script — even throwaway — MUST use PEP 723 inline metadata with the `# ─── How to run ───` comment block. No venv, no `requirements.txt`. The script IS the environment spec. A script without the usage comment block is incomplete.\n\nScaffold with: `uv run ../../scripts/python/new-script.py <name> --deps \"httpx2[http2,brotli,zstd]\"` (writes to temp dir by default, `--output` for specific path).\n\nLoad `one-liners.md` for full patterns, examples, and anti-patterns.\n\n## Reference loading\n\nLoad on demand — not all at once.\n\n| Need | Load |\n|---|---|\n| Full pyproject.toml config | `pyproject-strict.md` |\n| Type patterns (NewType, Final, enums, narrowing) | `type-patterns.md` |\n| Data modeling (container choice, frozen, parse-don't-validate) | `data-modeling.md` |\n| Error handling (typed errors, union returns, exhaustive match) | `error-handling.md` |\n| Async patterns (anyio) | `async-anyio.md` |\n| Data processing (polars / duckdb) | `data-processing.md` |\n| FastAPI + SQLAlchemy stack | `fastapi-stack.md` |\n| Library decision tree | `libraries.md` |\n| **httpx2 optimization** (MUST load for any network code) | `httpx2-optimization.md` |\n| **orjson** (when JSON is in the hot path; FastAPI/Pydantic v2 integration) | `orjson-stack.md` |\n| One-liner scripts (PEP 723) | `one-liners.md` |\n| PydanticAI agents | `pydantic-ai.md` |\n| Textual TUI | `textual-tui.md` |\n\n## httpx2 — mandatory for ALL network requests\n\nEvery outgoing HTTP call MUST use [`httpx2`](https://github.com/pydantic/httpx2) (`httpx2[http2,brotli,zstd]`). Never `requests`, never `aiohttp`, never the original `httpx`.\n\n**ALL optimizations are ON by default — not optional, not progressive, not \"nice to have\".** A bare `httpx2.AsyncClient()` is a bug — treat it like a lint violation. The correct way is the factory pattern in `httpx2-optimization.md` with: HTTP/2 enabled, tuned connection pool (200/40/30s), split timeouts (5/30/10/10), transport retries (3), TCP_NODELAY, follow_redirects, and event hooks for observability.\n\nWhen writing or reviewing ANY network code, **ALWAYS load `httpx2-optimization.md`** and use the factory pattern verbatim. No exceptions.\n\n## No-excuse audit\n\nViolations caught by `../../scripts/python/check-no-excuse-rules.py`. Run after every edit session.\n\n| Rule ID | Catches | Opt-out |\n|---|---|---|\n| `cast-any` | `cast(Any, ...)` | None — redesign types |\n| `type-ignore` | `# type: ignore` | None — fix the type |\n| `pyright-ignore` | `# pyright: ignore` | None — fix the type |\n| `bare-except` | `except:` with no class | None — name the exception |\n| `silent-except` | `except X: pass` / `except X: ...` | None — handle or re-raise |\n| `no-asyncio` | `import asyncio` | `# noqa: ANYIO_OK` |\n| `no-pandas` | `import pandas` | `# noqa: PANDAS_OK` |\n| `mutable-dataclass` | `@dataclass` without `frozen=True` | `# noqa: MUTABLE_OK` |\n| `missing-slots` | `@dataclass` without `slots=True` | `# noqa: SLOTS_OK` |\n| `raw-dict-return` | `-> dict` in function return type | `# noqa: DICT_OK` |\n| `missing-assert-never` | `match` block without `assert_never` default | `# noqa: MATCH_OK` |\n| `generic-exception` | `raise ValueError(\"...\")` / `raise TypeError(\"...\")` with bare string | `# noqa: GENERIC_ERR_OK` |\n| `no-object` | `object` used as type annotation (param, return, generic arg) | `# noqa: OBJECT_OK` |\n| `if-elif-on-variant` | `if isinstance()`/`if x == Enum.V` chain that should be `match/case` | `# noqa: IF_VARIANT_OK` |\n| `oversized-module` | File exceeds 250 pure LOC (non-blank, non-comment) | `# noqa: SIZE_OK` |\n| `broad-except` | `except Exception` / `except BaseException` (too broad) | `# noqa: BROAD_EXCEPT_OK` |\n\nFix every violation before declaring work done. basedpyright + ruff strict config catches the rest.\n\n## In tests\n\nTests are strict too, with these exceptions (already configured in `pyproject.toml` per-file-ignores):\n\n| In tests you may | Why |\n|---|---|\n| Use `assert` | That's how pytest works (`S101` ignored) |\n| Use magic numbers | Test data (`PLR2004` ignored) |\n| Access `_private` members | Testing internals (`SLF001` ignored) |\n| Skip docstrings | Test names are the docs (`D` ignored) |\n| Have unused function args | Fixtures (`ARG` ignored) |\n\nTests still follow the iron list — frozen dataclasses, typed errors, exhaustive match. If test fixtures need mutable state, use `# noqa: MUTABLE_OK` on the fixture class.\n\n## Existing codebases\n\nWhen editing an existing file that doesn't follow these rules: **write new code in strict style, don't refactor existing code in the same change.** Mixing feature work with style migration makes reviews harder and bugs likelier.\n\n## Activation\n\nThis skill activates whenever you are writing or modifying any `.py` file. Even one-off scripts get the strict treatment — that is the whole point of PEP 723 + uv: production hygiene with throwaway ergonomics.\n","exit_code":0,"duration":{"secs":0,"nanos":83719102},"formatted_output":"\n# Python Programmer\n\nModern Python. Type-strict, stack-first, async-correct.\n\n## Philosophy\n\nThe type checker is your compiler. Make illegal states unrepresentable. Parse at boundaries. Own resources explicitly. Every function has a contract; the type system enforces it.\n\n## Hard rules\n\nThese are deliberate project choices. Violations are always wrong, not \"style preferences\".\n\n### Tooling\n\n| Category | Use | Never |\n|---|---|---|\n| Package manager | `uv` | pip, poetry, conda, pipenv |\n| Type checker | `basedpyright` (`typeCheckingMode = \"all\"`) | pyright, mypy |\n| Linter + formatter | `ruff` (`select = [\"ALL\"]`) | flake8, black, isort, autopep8 |\n| Async runtime | `anyio` | `import asyncio` |\n| Data | `polars` + `duckdb` + `numpy` | pandas |\n| Web framework | FastAPI + Pydantic v2 | Flask, Django REST |\n| ORM | SQLAlchemy 2.x async | Django ORM, Tortoise |\n| HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) | requests, aiohttp, httpx |\n| Testing | `pytest` | unittest |\n| CLI | `typer` + `rich` | argparse, click, fire |\n\n### The iron list\n\n1. **Frozen by default** — `@dataclass(frozen=True, slots=True)`. Pydantic: `model_config = ConfigDict(frozen=True)`. Mutable only when mutation is the documented purpose.\n2. **NewType for distinct IDs** — `UserId = NewType(\"UserId\", int)`. Never pass raw `int` where a branded type exists.\n3. **`match` only for variants, `if` only for booleans** — **NEVER** use `if/elif/else` to discriminate on type (`isinstance`), enum value, or literal variant. `match/case` is mandatory for these — non-negotiable. **ALWAYS** end with `case unreachable: assert_never(unreachable)` — bare `case _: pass` and `case _: raise ValueError` are banned (they silently swallow new variants). `if/else` is fine only for boolean expressions, range checks, and predicate calls that aren't variant discrimination. See \"Why `if/elif` on variants is banned\" below for examples.\n4. **Protocol over ABC** — `typing.Protocol` for interfaces. ABC only when you need shared method implementation.\n5. **No raw dicts in signatures** — params and returns use `TypedDict`, `dataclass`, or Pydantic model. Internal scratch dicts are fine.\n6. **Parse, don't validate** — constructors produce typed objects or raise. Never pass unvalidated data deeper into the call stack.\n7. **Typed errors** — error types are dataclasses or exceptions with typed fields. Never `raise ValueError(\"something\")` with a bare string. Use union returns when the caller is within 1-2 call levels and must handle the outcome (repository → service). Use exceptions when the error should propagate up many layers to a boundary handler (service → HTTP handler).\n8. **Final for constants** — module-level constants use `Final`. Mutable module globals are a code smell.\n9. **Explicit None** — annotate `-> X | None`. Never return `None` from a function whose signature omits it.\n10. **Context managers for resources** — files, DB connections, HTTP clients, locks. No manual `.close()`.\n11. **No Any, no object** — both are banned as type annotations. `object` erases all structural information (zero callable attributes, zero narrowing). Use `Protocol` (structural typing), `TypeVar` (generic pass-through), explicit union (known variants), or `TypedDict` (dict shapes).\n12. **No cast** — `cast()` is banned. Redesign the types.\n13. **No type: ignore** — fix the type error. The checker is right; you are wrong.\n14. **No broad except** — `except Exception` and `except BaseException` are banned. Catch the **specific** exception you expect. A broad catch swallows bugs you need to see — `KeyError`, `AttributeError`, `TypeError` all vanish silently. If you genuinely need a catch-all at a top-level boundary (CLI entry, HTTP handler), use `# noqa: BROAD_EXCEPT_OK` and log + re-raise.\n\n### Typing and safety\n\n- `basedpyright` in `typeCheckingMode = \"all\"`. Every public function has full annotations. Internal helpers: annotate return type; parameter types may be inferred.\n- `ruff` with `select = [\"ALL\"]`. Override specific rules per project in `pyproject.toml`, never globally disable the strict baseline.\n- Every new function must have a `docstring` unless its name + signature makes it completely obvious (e.g. `def full_name(first: str, last: str) -> str:`).\n- Use `X | Y` union syntax (PEP 604), never `Union[X, Y]` or `Optional[X]`.\n\n### Why `object` is banned\n\n`object` pretends to be safe (\"it's the top type!\") but gives **zero** narrowing and **zero** attributes. Even `Any` is more honest — it admits the boundary is untyped.\n\n```python\n# BANNED\ndef process(data: object) -> object: ...\ndef store(items: list[object]) -> None: ...\nresults: dict[str, object] = {}\n\n# GOOD — Protocol for structural typing\nclass Serializable(Protocol):\n def serialize(self) -> bytes: ...\ndef process(data: Serializable) -> ProcessResult: ...\n\n# GOOD — TypeVar for generic pass-through\ndef identity[T](x: T) -> T: ...\ndef first[T](items: Sequence[T]) -> T: ...\n\n# GOOD — explicit union for known variants\ndef parse(raw: str | bytes) -> Document: ...\n```\n\n### Why `if/elif` on variants is banned\n\n`if/elif/else` chains on type, enum, or literal values lose compile-time exhaustiveness. When a new variant is added, nothing warns you. `match/case` + `assert_never` does.\n\n```python\n# BANNED — if/elif for type discrimination\nif isinstance(event, Click):\n handle_click(event.x, event.y)\nelif isinstance(event, Scroll):\n handle_scroll(event.delta)\nelse:\n raise ValueError(f\"Unknown: {event}\") # runtime bomb\n\n# BANNED — if/elif for enum discrimination\nif status == Status.PENDING:\n start_review()\nelif status == Status.ACTIVE:\n continue_processing()\nelif status == Status.CLOSED:\n archive()\n\n# BANNED — non-exhaustive match (swallows new variants)\nmatch event:\n case Click(x, y): handle_click(x, y)\n case _: pass\n\n# GOOD — exhaustive match with assert_never\nmatch event:\n case Click(x=x, y=y):\n handle_click(x, y)\n case Scroll(delta=delta):\n handle_scroll(delta)\n case unreachable:\n assert_never(unreachable)\n\n# GOOD — enum match\nmatch status:\n case Status.PENDING: start_review()\n case Status.ACTIVE: continue_processing()\n case Status.CLOSED: archive()\n case unreachable: assert_never(unreachable)\n```\n\n`if/else` is fine for boolean conditions and range checks — things that aren't variant discrimination:\n\n```python\n# FINE — boolean, not variant\nif age >= 18:\n grant_access()\nelse:\n deny_access()\n```\n\n### Why broad `except` is banned\n\n`except Exception` catches **every** non-system exception — `KeyError`, `TypeError`, `AttributeError`, `ValueError` all vanish. You lose the stack trace that would have told you exactly what went wrong. The fix is always to name the exception you expect.\n\n```python\n# BANNED — swallows bugs\ntry:\n result = api.fetch(url)\nexcept Exception as e:\n logger.error(e)\n return None\n\n# BANNED — catch-and-ignore\ntry:\n parse(data)\nexcept Exception:\n pass\n\n# GOOD — catch what you expect\ntry:\n result = api.fetch(url)\nexcept httpx.HTTPStatusError as e:\n logger.error(\"API %d: %s\", e.response.status_code, e.request.url)\n return None\nexcept httpx.ConnectError:\n raise ServiceUnavailableError(service=\"api\") from None\n\n# GOOD — top-level boundary (only place broad catch is acceptable)\ndef main() -> int: # noqa: BROAD_EXCEPT_OK\n try:\n return run()\n except Exception:\n logger.exception(\"unhandled error\")\n return 1\n```\n\n### Async\n\n- `import asyncio` is **BANNED**. Use `import anyio`.\n- For background tasks, use `anyio.create_task_group`. Never fire-and-forget with `asyncio.create_task`.\n- For concurrency gates, use `anyio.CapacityLimiter` (not `asyncio.Semaphore`).\n- Load `async-anyio.md` when writing async code for the full pattern library.\n\n### Data modeling — which container, when\n\nAll model fields carry type annotations. No `Any`, no untyped dicts in public APIs.\nUse `polars` + `duckdb` for data. pandas is never the right answer in this stack.\n\n| Situation | Use |\n|---|---|\n| User input, API request/response | `Pydantic BaseModel (frozen=True)` |\n| Internal value object (no I/O) | `@dataclass(frozen=True, slots=True)` |\n| Function with multiple outcomes | Union of frozen dataclasses + `match` |\n| Dict shape for JSON compat / `**kwargs` | `TypedDict` |\n| Fixed constants | `StrEnum` / `IntEnum` |\n| Distinct primitive (UserId vs MovieId) | `NewType` |\n| Contract / capability | `Protocol` |\n| Contract + shared implementation | `ABC` |\n| ORM model (SQLAlchemy) | `Mapped[]` — inherently mutable, `# noqa: MUTABLE_OK` |\n| Config from env vars | `pydantic-settings BaseSettings` |\n\n**The one rule**: data crosses trust boundary → Pydantic. Everything else → dataclass.\n\nLoad `data-modeling.md` for the full decision flowchart and comparison matrix.\n\n### When frozen=True does not apply\n\n- **ORM models** — SQLAlchemy `Mapped[]` requires mutation. Use `# noqa: MUTABLE_OK`.\n- **Builder / accumulator** — object exists to be mutated (counter, buffer, state machine). Docstring must explain why.\n- **Pydantic Settings** — tests override fields. Mutable is acceptable.\n\nIf you need `# noqa: MUTABLE_OK`, the class docstring must say why mutation is required.\n\n### Libraries\n\nCanonical defaults (override only if `pyproject.toml` explicitly picks something else):\n\n| Domain | Library | Reason |\n|---|---|---|\n| CLI | `typer` | Type-annotated CLI from function sigs |\n| Pretty output | `rich` | Tables, progress, tracebacks, markdown |\n| HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) | Next-gen HTTP client (Pydantic stewardship), HTTP/2, brotli+zstd. Always `httpx2[http2,brotli,zstd]`. See `httpx2-optimization.md` |\n| Validation | `pydantic` v2 | Fast native validator, JSON Schema |\n| Web API | `fastapi` | Async, Pydantic-native, OpenAPI |\n| ORM | `sqlalchemy` 2.x async | `Mapped[]` types, async sessions |\n| DB driver (Postgres) | `asyncpg` (via SQLAlchemy) | Fastest PG driver |\n| AI agents | `pydantic-ai` | Typed deps, structured output |\n| TUI | `textual` | Rich-based, CSS layout, widgets |\n| Logging | `rich.logging.RichHandler` | Pretty; swap to `structlog` in prod |\n\n## pyproject.toml — the one true config\n\nScaffold a new project with all strict defaults pre-configured:\n\n```bash\nuv run ../../scripts/python/new-project.py myproject\nuv run ../../scripts/python/new-project.py myproject --path ./workspace\nuv run ../../scripts/python/new-project.py myproject --lib # publishable library\n```\n\nCreates via `uv init`, then injects basedpyright `typeCheckingMode = \"all\"` + ruff `select = [\"ALL\"]` + pytest strict. Cross-platform (macOS, Linux, Windows).\n\nFor manual setup: `uv init --app myproject`, then load `pyproject-strict.md`.\n\n## PEP 723 — inline script metadata (mandatory for ALL scripts)\n\nEvery `.py` script — even throwaway — MUST use PEP 723 inline metadata with the `# ─── How to run ───` comment block. No venv, no `requirements.txt`. The script IS the environment spec. A script without the usage comment block is incomplete.\n\nScaffold with: `uv run ../../scripts/python/new-script.py <name> --deps \"httpx2[http2,brotli,zstd]\"` (writes to temp dir by default, `--output` for specific path).\n\nLoad `one-liners.md` for full patterns, examples, and anti-patterns.\n\n## Reference loading\n\nLoad on demand — not all at once.\n\n| Need | Load |\n|---|---|\n| Full pyproject.toml config | `pyproject-strict.md` |\n| Type patterns (NewType, Final, enums, narrowing) | `type-patterns.md` |\n| Data modeling (container choice, frozen, parse-don't-validate) | `data-modeling.md` |\n| Error handling (typed errors, union returns, exhaustive match) | `error-handling.md` |\n| Async patterns (anyio) | `async-anyio.md` |\n| Data processing (polars / duckdb) | `data-processing.md` |\n| FastAPI + SQLAlchemy stack | `fastapi-stack.md` |\n| Library decision tree | `libraries.md` |\n| **httpx2 optimization** (MUST load for any network code) | `httpx2-optimization.md` |\n| **orjson** (when JSON is in the hot path; FastAPI/Pydantic v2 integration) | `orjson-stack.md` |\n| One-liner scripts (PEP 723) | `one-liners.md` |\n| PydanticAI agents | `pydantic-ai.md` |\n| Textual TUI | `textual-tui.md` |\n\n## httpx2 — mandatory for ALL network requests\n\nEvery outgoing HTTP call MUST use [`httpx2`](https://github.com/pydantic/httpx2) (`httpx2[http2,brotli,zstd]`). Never `requests`, never `aiohttp`, never the original `httpx`.\n\n**ALL optimizations are ON by default — not optional, not progressive, not \"nice to have\".** A bare `httpx2.AsyncClient()` is a bug — treat it like a lint violation. The correct way is the factory pattern in `httpx2-optimization.md` with: HTTP/2 enabled, tuned connection pool (200/40/30s), split timeouts (5/30/10/10), transport retries (3), TCP_NODELAY, follow_redirects, and event hooks for observability.\n\nWhen writing or reviewing ANY network code, **ALWAYS load `httpx2-optimization.md`** and use the factory pattern verbatim. No exceptions.\n\n## No-excuse audit\n\nViolations caught by `../../scripts/python/check-no-excuse-rules.py`. Run after every edit session.\n\n| Rule ID | Catches | Opt-out |\n|---|---|---|\n| `cast-any` | `cast(Any, ...)` | None — redesign types |\n| `type-ignore` | `# type: ignore` | None — fix the type |\n| `pyright-ignore` | `# pyright: ignore` | None — fix the type |\n| `bare-except` | `except:` with no class | None — name the exception |\n| `silent-except` | `except X: pass` / `except X: ...` | None — handle or re-raise |\n| `no-asyncio` | `import asyncio` | `# noqa: ANYIO_OK` |\n| `no-pandas` | `import pandas` | `# noqa: PANDAS_OK` |\n| `mutable-dataclass` | `@dataclass` without `frozen=True` | `# noqa: MUTABLE_OK` |\n| `missing-slots` | `@dataclass` without `slots=True` | `# noqa: SLOTS_OK` |\n| `raw-dict-return` | `-> dict` in function return type | `# noqa: DICT_OK` |\n| `missing-assert-never` | `match` block without `assert_never` default | `# noqa: MATCH_OK` |\n| `generic-exception` | `raise ValueError(\"...\")` / `raise TypeError(\"...\")` with bare string | `# noqa: GENERIC_ERR_OK` |\n| `no-object` | `object` used as type annotation (param, return, generic arg) | `# noqa: OBJECT_OK` |\n| `if-elif-on-variant` | `if isinstance()`/`if x == Enum.V` chain that should be `match/case` | `# noqa: IF_VARIANT_OK` |\n| `oversized-module` | File exceeds 250 pure LOC (non-blank, non-comment) | `# noqa: SIZE_OK` |\n| `broad-except` | `except Exception` / `except BaseException` (too broad) | `# noqa: BROAD_EXCEPT_OK` |\n\nFix every violation before declaring work done. basedpyright + ruff strict config catches the rest.\n\n## In tests\n\nTests are strict too, with these exceptions (already configured in `pyproject.toml` per-file-ignores):\n\n| In tests you may | Why |\n|---|---|\n| Use `assert` | That's how pytest works (`S101` ignored) |\n| Use magic numbers | Test data (`PLR2004` ignored) |\n| Access `_private` members | Testing internals (`SLF001` ignored) |\n| Skip docstrings | Test names are the docs (`D` ignored) |\n| Have unused function args | Fixtures (`ARG` ignored) |\n\nTests still follow the iron list — frozen dataclasses, typed errors, exhaustive match. If test fixtures need mutable state, use `# noqa: MUTABLE_OK` on the fixture class.\n\n## Existing codebases\n\nWhen editing an existing file that doesn't follow these rules: **write new code in strict style, don't refactor existing code in the same change.** Mixing feature work with style migration makes reviews harder and bugs likelier.\n\n## Activation\n\nThis skill activates whenever you are writing or modifying any `.py` file. Even one-off scripts get the strict treatment — that is the whole point of PEP 723 + uv: production hygiene with throwaway ergonomics.\n"},"started_at_ms":1789012334829,"completed_at_ms":1789012334912}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:52:14.913Z","ordinal":36,"type":"event_msg","payload":{"type":"item_completed","thread_id":"01a08971-6519-7cf3-9399-e7f6b9686fbc","turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","item":{"type":"CommandExecution","id":"exec-072e5b26-5eb4-4ef5-af3b-adbee0aebf67","process_id":"47164","command":["/usr/bin/bash","-lc","cat /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/sisyphuslabs/omo/4.16.1/skills/programming/references/python/README.md"],"cwd":"file:///lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/kitchen","parsed_cmd":[{"type":"read","cmd":"cat /lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/sisyphuslabs/omo/4.16.1/skills/programming/references/python/README.md","name":"README.md","path":"/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/.codex/plugins/cache/sisyphuslabs/omo/4.16.1/skills/programming/references/python/README.md"}],"source":"unified_exec_startup","status":"completed","stdout":"\n# Python Programmer\n\nModern Python. Type-strict, stack-first, async-correct.\n\n## Philosophy\n\nThe type checker is your compiler. Make illegal states unrepresentable. Parse at boundaries. Own resources explicitly. Every function has a contract; the type system enforces it.\n\n## Hard rules\n\nThese are deliberate project choices. Violations are always wrong, not \"style preferences\".\n\n### Tooling\n\n| Category | Use | Never |\n|---|---|---|\n| Package manager | `uv` | pip, poetry, conda, pipenv |\n| Type checker | `basedpyright` (`typeCheckingMode = \"all\"`) | pyright, mypy |\n| Linter + formatter | `ruff` (`select = [\"ALL\"]`) | flake8, black, isort, autopep8 |\n| Async runtime | `anyio` | `import asyncio` |\n| Data | `polars` + `duckdb` + `numpy` | pandas |\n| Web framework | FastAPI + Pydantic v2 | Flask, Django REST |\n| ORM | SQLAlchemy 2.x async | Django ORM, Tortoise |\n| HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) | requests, aiohttp, httpx |\n| Testing | `pytest` | unittest |\n| CLI | `typer` + `rich` | argparse, click, fire |\n\n### The iron list\n\n1. **Frozen by default** — `@dataclass(frozen=True, slots=True)`. Pydantic: `model_config = ConfigDict(frozen=True)`. Mutable only when mutation is the documented purpose.\n2. **NewType for distinct IDs** — `UserId = NewType(\"UserId\", int)`. Never pass raw `int` where a branded type exists.\n3. **`match` only for variants, `if` only for booleans** — **NEVER** use `if/elif/else` to discriminate on type (`isinstance`), enum value, or literal variant. `match/case` is mandatory for these — non-negotiable. **ALWAYS** end with `case unreachable: assert_never(unreachable)` — bare `case _: pass` and `case _: raise ValueError` are banned (they silently swallow new variants). `if/else` is fine only for boolean expressions, range checks, and predicate calls that aren't variant discrimination. See \"Why `if/elif` on variants is banned\" below for examples.\n4. **Protocol over ABC** — `typing.Protocol` for interfaces. ABC only when you need shared method implementation.\n5. **No raw dicts in signatures** — params and returns use `TypedDict`, `dataclass`, or Pydantic model. Internal scratch dicts are fine.\n6. **Parse, don't validate** — constructors produce typed objects or raise. Never pass unvalidated data deeper into the call stack.\n7. **Typed errors** — error types are dataclasses or exceptions with typed fields. Never `raise ValueError(\"something\")` with a bare string. Use union returns when the caller is within 1-2 call levels and must handle the outcome (repository → service). Use exceptions when the error should propagate up many layers to a boundary handler (service → HTTP handler).\n8. **Final for constants** — module-level constants use `Final`. Mutable module globals are a code smell.\n9. **Explicit None** — annotate `-> X | None`. Never return `None` from a function whose signature omits it.\n10. **Context managers for resources** — files, DB connections, HTTP clients, locks. No manual `.close()`.\n11. **No Any, no object** — both are banned as type annotations. `object` erases all structural information (zero callable attributes, zero narrowing). Use `Protocol` (structural typing), `TypeVar` (generic pass-through), explicit union (known variants), or `TypedDict` (dict shapes).\n12. **No cast** — `cast()` is banned. Redesign the types.\n13. **No type: ignore** — fix the type error. The checker is right; you are wrong.\n14. **No broad except** — `except Exception` and `except BaseException` are banned. Catch the **specific** exception you expect. A broad catch swallows bugs you need to see — `KeyError`, `AttributeError`, `TypeError` all vanish silently. If you genuinely need a catch-all at a top-level boundary (CLI entry, HTTP handler), use `# noqa: BROAD_EXCEPT_OK` and log + re-raise.\n\n### Typing and safety\n\n- `basedpyright` in `typeCheckingMode = \"all\"`. Every public function has full annotations. Internal helpers: annotate return type; parameter types may be inferred.\n- `ruff` with `select = [\"ALL\"]`. Override specific rules per project in `pyproject.toml`, never globally disable the strict baseline.\n- Every new function must have a `docstring` unless its name + signature makes it completely obvious (e.g. `def full_name(first: str, last: str) -> str:`).\n- Use `X | Y` union syntax (PEP 604), never `Union[X, Y]` or `Optional[X]`.\n\n### Why `object` is banned\n\n`object` pretends to be safe (\"it's the top type!\") but gives **zero** narrowing and **zero** attributes. Even `Any` is more honest — it admits the boundary is untyped.\n\n```python\n# BANNED\ndef process(data: object) -> object: ...\ndef store(items: list[object]) -> None: ...\nresults: dict[str, object] = {}\n\n# GOOD — Protocol for structural typing\nclass Serializable(Protocol):\n def serialize(self) -> bytes: ...\ndef process(data: Serializable) -> ProcessResult: ...\n\n# GOOD — TypeVar for generic pass-through\ndef identity[T](x: T) -> T: ...\ndef first[T](items: Sequence[T]) -> T: ...\n\n# GOOD — explicit union for known variants\ndef parse(raw: str | bytes) -> Document: ...\n```\n\n### Why `if/elif` on variants is banned\n\n`if/elif/else` chains on type, enum, or literal values lose compile-time exhaustiveness. When a new variant is added, nothing warns you. `match/case` + `assert_never` does.\n\n```python\n# BANNED — if/elif for type discrimination\nif isinstance(event, Click):\n handle_click(event.x, event.y)\nelif isinstance(event, Scroll):\n handle_scroll(event.delta)\nelse:\n raise ValueError(f\"Unknown: {event}\") # runtime bomb\n\n# BANNED — if/elif for enum discrimination\nif status == Status.PENDING:\n start_review()\nelif status == Status.ACTIVE:\n continue_processing()\nelif status == Status.CLOSED:\n archive()\n\n# BANNED — non-exhaustive match (swallows new variants)\nmatch event:\n case Click(x, y): handle_click(x, y)\n case _: pass\n\n# GOOD — exhaustive match with assert_never\nmatch event:\n case Click(x=x, y=y):\n handle_click(x, y)\n case Scroll(delta=delta):\n handle_scroll(delta)\n case unreachable:\n assert_never(unreachable)\n\n# GOOD — enum match\nmatch status:\n case Status.PENDING: start_review()\n case Status.ACTIVE: continue_processing()\n case Status.CLOSED: archive()\n case unreachable: assert_never(unreachable)\n```\n\n`if/else` is fine for boolean conditions and range checks — things that aren't variant discrimination:\n\n```python\n# FINE — boolean, not variant\nif age >= 18:\n grant_access()\nelse:\n deny_access()\n```\n\n### Why broad `except` is banned\n\n`except Exception` catches **every** non-system exception — `KeyError`, `TypeError`, `AttributeError`, `ValueError` all vanish. You lose the stack trace that would have told you exactly what went wrong. The fix is always to name the exception you expect.\n\n```python\n# BANNED — swallows bugs\ntry:\n result = api.fetch(url)\nexcept Exception as e:\n logger.error(e)\n return None\n\n# BANNED — catch-and-ignore\ntry:\n parse(data)\nexcept Exception:\n pass\n\n# GOOD — catch what you expect\ntry:\n result = api.fetch(url)\nexcept httpx.HTTPStatusError as e:\n logger.error(\"API %d: %s\", e.response.status_code, e.request.url)\n return None\nexcept httpx.ConnectError:\n raise ServiceUnavailableError(service=\"api\") from None\n\n# GOOD — top-level boundary (only place broad catch is acceptable)\ndef main() -> int: # noqa: BROAD_EXCEPT_OK\n try:\n return run()\n except Exception:\n logger.exception(\"unhandled error\")\n return 1\n```\n\n### Async\n\n- `import asyncio` is **BANNED**. Use `import anyio`.\n- For background tasks, use `anyio.create_task_group`. Never fire-and-forget with `asyncio.create_task`.\n- For concurrency gates, use `anyio.CapacityLimiter` (not `asyncio.Semaphore`).\n- Load `async-anyio.md` when writing async code for the full pattern library.\n\n### Data modeling — which container, when\n\nAll model fields carry type annotations. No `Any`, no untyped dicts in public APIs.\nUse `polars` + `duckdb` for data. pandas is never the right answer in this stack.\n\n| Situation | Use |\n|---|---|\n| User input, API request/response | `Pydantic BaseModel (frozen=True)` |\n| Internal value object (no I/O) | `@dataclass(frozen=True, slots=True)` |\n| Function with multiple outcomes | Union of frozen dataclasses + `match` |\n| Dict shape for JSON compat / `**kwargs` | `TypedDict` |\n| Fixed constants | `StrEnum` / `IntEnum` |\n| Distinct primitive (UserId vs MovieId) | `NewType` |\n| Contract / capability | `Protocol` |\n| Contract + shared implementation | `ABC` |\n| ORM model (SQLAlchemy) | `Mapped[]` — inherently mutable, `# noqa: MUTABLE_OK` |\n| Config from env vars | `pydantic-settings BaseSettings` |\n\n**The one rule**: data crosses trust boundary → Pydantic. Everything else → dataclass.\n\nLoad `data-modeling.md` for the full decision flowchart and comparison matrix.\n\n### When frozen=True does not apply\n\n- **ORM models** — SQLAlchemy `Mapped[]` requires mutation. Use `# noqa: MUTABLE_OK`.\n- **Builder / accumulator** — object exists to be mutated (counter, buffer, state machine). Docstring must explain why.\n- **Pydantic Settings** — tests override fields. Mutable is acceptable.\n\nIf you need `# noqa: MUTABLE_OK`, the class docstring must say why mutation is required.\n\n### Libraries\n\nCanonical defaults (override only if `pyproject.toml` explicitly picks something else):\n\n| Domain | Library | Reason |\n|---|---|---|\n| CLI | `typer` | Type-annotated CLI from function sigs |\n| Pretty output | `rich` | Tables, progress, tracebacks, markdown |\n| HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) | Next-gen HTTP client (Pydantic stewardship), HTTP/2, brotli+zstd. Always `httpx2[http2,brotli,zstd]`. See `httpx2-optimization.md` |\n| Validation | `pydantic` v2 | Fast native validator, JSON Schema |\n| Web API | `fastapi` | Async, Pydantic-native, OpenAPI |\n| ORM | `sqlalchemy` 2.x async | `Mapped[]` types, async sessions |\n| DB driver (Postgres) | `asyncpg` (via SQLAlchemy) | Fastest PG driver |\n| AI agents | `pydantic-ai` | Typed deps, structured output |\n| TUI | `textual` | Rich-based, CSS layout, widgets |\n| Logging | `rich.logging.RichHandler` | Pretty; swap to `structlog` in prod |\n\n## pyproject.toml — the one true config\n\nScaffold a new project with all strict defaults pre-configured:\n\n```bash\nuv run ../../scripts/python/new-project.py myproject\nuv run ../../scripts/python/new-project.py myproject --path ./workspace\nuv run ../../scripts/python/new-project.py myproject --lib # publishable library\n```\n\nCreates via `uv init`, then injects basedpyright `typeCheckingMode = \"all\"` + ruff `select = [\"ALL\"]` + pytest strict. Cross-platform (macOS, Linux, Windows).\n\nFor manual setup: `uv init --app myproject`, then load `pyproject-strict.md`.\n\n## PEP 723 — inline script metadata (mandatory for ALL scripts)\n\nEvery `.py` script — even throwaway — MUST use PEP 723 inline metadata with the `# ─── How to run ───` comment block. No venv, no `requirements.txt`. The script IS the environment spec. A script without the usage comment block is incomplete.\n\nScaffold with: `uv run ../../scripts/python/new-script.py <name> --deps \"httpx2[http2,brotli,zstd]\"` (writes to temp dir by default, `--output` for specific path).\n\nLoad `one-liners.md` for full patterns, examples, and anti-patterns.\n\n## Reference loading\n\nLoad on demand — not all at once.\n\n| Need | Load |\n|---|---|\n| Full pyproject.toml config | `pyproject-strict.md` |\n| Type patterns (NewType, Final, enums, narrowing) | `type-patterns.md` |\n| Data modeling (container choice, frozen, parse-don't-validate) | `data-modeling.md` |\n| Error handling (typed errors, union returns, exhaustive match) | `error-handling.md` |\n| Async patterns (anyio) | `async-anyio.md` |\n| Data processing (polars / duckdb) | `data-processing.md` |\n| FastAPI + SQLAlchemy stack | `fastapi-stack.md` |\n| Library decision tree | `libraries.md` |\n| **httpx2 optimization** (MUST load for any network code) | `httpx2-optimization.md` |\n| **orjson** (when JSON is in the hot path; FastAPI/Pydantic v2 integration) | `orjson-stack.md` |\n| One-liner scripts (PEP 723) | `one-liners.md` |\n| PydanticAI agents | `pydantic-ai.md` |\n| Textual TUI | `textual-tui.md` |\n\n## httpx2 — mandatory for ALL network requests\n\nEvery outgoing HTTP call MUST use [`httpx2`](https://github.com/pydantic/httpx2) (`httpx2[http2,brotli,zstd]`). Never `requests`, never `aiohttp`, never the original `httpx`.\n\n**ALL optimizations are ON by default — not optional, not progressive, not \"nice to have\".** A bare `httpx2.AsyncClient()` is a bug — treat it like a lint violation. The correct way is the factory pattern in `httpx2-optimization.md` with: HTTP/2 enabled, tuned connection pool (200/40/30s), split timeouts (5/30/10/10), transport retries (3), TCP_NODELAY, follow_redirects, and event hooks for observability.\n\nWhen writing or reviewing ANY network code, **ALWAYS load `httpx2-optimization.md`** and use the factory pattern verbatim. No exceptions.\n\n## No-excuse audit\n\nViolations caught by `../../scripts/python/check-no-excuse-rules.py`. Run after every edit session.\n\n| Rule ID | Catches | Opt-out |\n|---|---|---|\n| `cast-any` | `cast(Any, ...)` | None — redesign types |\n| `type-ignore` | `# type: ignore` | None — fix the type |\n| `pyright-ignore` | `# pyright: ignore` | None — fix the type |\n| `bare-except` | `except:` with no class | None — name the exception |\n| `silent-except` | `except X: pass` / `except X: ...` | None — handle or re-raise |\n| `no-asyncio` | `import asyncio` | `# noqa: ANYIO_OK` |\n| `no-pandas` | `import pandas` | `# noqa: PANDAS_OK` |\n| `mutable-dataclass` | `@dataclass` without `frozen=True` | `# noqa: MUTABLE_OK` |\n| `missing-slots` | `@dataclass` without `slots=True` | `# noqa: SLOTS_OK` |\n| `raw-dict-return` | `-> dict` in function return type | `# noqa: DICT_OK` |\n| `missing-assert-never` | `match` block without `assert_never` default | `# noqa: MATCH_OK` |\n| `generic-exception` | `raise ValueError(\"...\")` / `raise TypeError(\"...\")` with bare string | `# noqa: GENERIC_ERR_OK` |\n| `no-object` | `object` used as type annotation (param, return, generic arg) | `# noqa: OBJECT_OK` |\n| `if-elif-on-variant` | `if isinstance()`/`if x == Enum.V` chain that should be `match/case` | `# noqa: IF_VARIANT_OK` |\n| `oversized-module` | File exceeds 250 pure LOC (non-blank, non-comment) | `# noqa: SIZE_OK` |\n| `broad-except` | `except Exception` / `except BaseException` (too broad) | `# noqa: BROAD_EXCEPT_OK` |\n\nFix every violation before declaring work done. basedpyright + ruff strict config catches the rest.\n\n## In tests\n\nTests are strict too, with these exceptions (already configured in `pyproject.toml` per-file-ignores):\n\n| In tests you may | Why |\n|---|---|\n| Use `assert` | That's how pytest works (`S101` ignored) |\n| Use magic numbers | Test data (`PLR2004` ignored) |\n| Access `_private` members | Testing internals (`SLF001` ignored) |\n| Skip docstrings | Test names are the docs (`D` ignored) |\n| Have unused function args | Fixtures (`ARG` ignored) |\n\nTests still follow the iron list — frozen dataclasses, typed errors, exhaustive match. If test fixtures need mutable state, use `# noqa: MUTABLE_OK` on the fixture class.\n\n## Existing codebases\n\nWhen editing an existing file that doesn't follow these rules: **write new code in strict style, don't refactor existing code in the same change.** Mixing feature work with style migration makes reviews harder and bugs likelier.\n\n## Activation\n\nThis skill activates whenever you are writing or modifying any `.py` file. Even one-off scripts get the strict treatment — that is the whole point of PEP 723 + uv: production hygiene with throwaway ergonomics.\n","stderr":"","aggregated_output":"\n# Python Programmer\n\nModern Python. Type-strict, stack-first, async-correct.\n\n## Philosophy\n\nThe type checker is your compiler. Make illegal states unrepresentable. Parse at boundaries. Own resources explicitly. Every function has a contract; the type system enforces it.\n\n## Hard rules\n\nThese are deliberate project choices. Violations are always wrong, not \"style preferences\".\n\n### Tooling\n\n| Category | Use | Never |\n|---|---|---|\n| Package manager | `uv` | pip, poetry, conda, pipenv |\n| Type checker | `basedpyright` (`typeCheckingMode = \"all\"`) | pyright, mypy |\n| Linter + formatter | `ruff` (`select = [\"ALL\"]`) | flake8, black, isort, autopep8 |\n| Async runtime | `anyio` | `import asyncio` |\n| Data | `polars` + `duckdb` + `numpy` | pandas |\n| Web framework | FastAPI + Pydantic v2 | Flask, Django REST |\n| ORM | SQLAlchemy 2.x async | Django ORM, Tortoise |\n| HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) | requests, aiohttp, httpx |\n| Testing | `pytest` | unittest |\n| CLI | `typer` + `rich` | argparse, click, fire |\n\n### The iron list\n\n1. **Frozen by default** — `@dataclass(frozen=True, slots=True)`. Pydantic: `model_config = ConfigDict(frozen=True)`. Mutable only when mutation is the documented purpose.\n2. **NewType for distinct IDs** — `UserId = NewType(\"UserId\", int)`. Never pass raw `int` where a branded type exists.\n3. **`match` only for variants, `if` only for booleans** — **NEVER** use `if/elif/else` to discriminate on type (`isinstance`), enum value, or literal variant. `match/case` is mandatory for these — non-negotiable. **ALWAYS** end with `case unreachable: assert_never(unreachable)` — bare `case _: pass` and `case _: raise ValueError` are banned (they silently swallow new variants). `if/else` is fine only for boolean expressions, range checks, and predicate calls that aren't variant discrimination. See \"Why `if/elif` on variants is banned\" below for examples.\n4. **Protocol over ABC** — `typing.Protocol` for interfaces. ABC only when you need shared method implementation.\n5. **No raw dicts in signatures** — params and returns use `TypedDict`, `dataclass`, or Pydantic model. Internal scratch dicts are fine.\n6. **Parse, don't validate** — constructors produce typed objects or raise. Never pass unvalidated data deeper into the call stack.\n7. **Typed errors** — error types are dataclasses or exceptions with typed fields. Never `raise ValueError(\"something\")` with a bare string. Use union returns when the caller is within 1-2 call levels and must handle the outcome (repository → service). Use exceptions when the error should propagate up many layers to a boundary handler (service → HTTP handler).\n8. **Final for constants** — module-level constants use `Final`. Mutable module globals are a code smell.\n9. **Explicit None** — annotate `-> X | None`. Never return `None` from a function whose signature omits it.\n10. **Context managers for resources** — files, DB connections, HTTP clients, locks. No manual `.close()`.\n11. **No Any, no object** — both are banned as type annotations. `object` erases all structural information (zero callable attributes, zero narrowing). Use `Protocol` (structural typing), `TypeVar` (generic pass-through), explicit union (known variants), or `TypedDict` (dict shapes).\n12. **No cast** — `cast()` is banned. Redesign the types.\n13. **No type: ignore** — fix the type error. The checker is right; you are wrong.\n14. **No broad except** — `except Exception` and `except BaseException` are banned. Catch the **specific** exception you expect. A broad catch swallows bugs you need to see — `KeyError`, `AttributeError`, `TypeError` all vanish silently. If you genuinely need a catch-all at a top-level boundary (CLI entry, HTTP handler), use `# noqa: BROAD_EXCEPT_OK` and log + re-raise.\n\n### Typing and safety\n\n- `basedpyright` in `typeCheckingMode = \"all\"`. Every public function has full annotations. Internal helpers: annotate return type; parameter types may be inferred.\n- `ruff` with `select = [\"ALL\"]`. Override specific rules per project in `pyproject.toml`, never globally disable the strict baseline.\n- Every new function must have a `docstring` unless its name + signature makes it completely obvious (e.g. `def full_name(first: str, last: str) -> str:`).\n- Use `X | Y` union syntax (PEP 604), never `Union[X, Y]` or `Optional[X]`.\n\n### Why `object` is banned\n\n`object` pretends to be safe (\"it's the top type!\") but gives **zero** narrowing and **zero** attributes. Even `Any` is more honest — it admits the boundary is untyped.\n\n```python\n# BANNED\ndef process(data: object) -> object: ...\ndef store(items: list[object]) -> None: ...\nresults: dict[str, object] = {}\n\n# GOOD — Protocol for structural typing\nclass Serializable(Protocol):\n def serialize(self) -> bytes: ...\ndef process(data: Serializable) -> ProcessResult: ...\n\n# GOOD — TypeVar for generic pass-through\ndef identity[T](x: T) -> T: ...\ndef first[T](items: Sequence[T]) -> T: ...\n\n# GOOD — explicit union for known variants\ndef parse(raw: str | bytes) -> Document: ...\n```\n\n### Why `if/elif` on variants is banned\n\n`if/elif/else` chains on type, enum, or literal values lose compile-time exhaustiveness. When a new variant is added, nothing warns you. `match/case` + `assert_never` does.\n\n```python\n# BANNED — if/elif for type discrimination\nif isinstance(event, Click):\n handle_click(event.x, event.y)\nelif isinstance(event, Scroll):\n handle_scroll(event.delta)\nelse:\n raise ValueError(f\"Unknown: {event}\") # runtime bomb\n\n# BANNED — if/elif for enum discrimination\nif status == Status.PENDING:\n start_review()\nelif status == Status.ACTIVE:\n continue_processing()\nelif status == Status.CLOSED:\n archive()\n\n# BANNED — non-exhaustive match (swallows new variants)\nmatch event:\n case Click(x, y): handle_click(x, y)\n case _: pass\n\n# GOOD — exhaustive match with assert_never\nmatch event:\n case Click(x=x, y=y):\n handle_click(x, y)\n case Scroll(delta=delta):\n handle_scroll(delta)\n case unreachable:\n assert_never(unreachable)\n\n# GOOD — enum match\nmatch status:\n case Status.PENDING: start_review()\n case Status.ACTIVE: continue_processing()\n case Status.CLOSED: archive()\n case unreachable: assert_never(unreachable)\n```\n\n`if/else` is fine for boolean conditions and range checks — things that aren't variant discrimination:\n\n```python\n# FINE — boolean, not variant\nif age >= 18:\n grant_access()\nelse:\n deny_access()\n```\n\n### Why broad `except` is banned\n\n`except Exception` catches **every** non-system exception — `KeyError`, `TypeError`, `AttributeError`, `ValueError` all vanish. You lose the stack trace that would have told you exactly what went wrong. The fix is always to name the exception you expect.\n\n```python\n# BANNED — swallows bugs\ntry:\n result = api.fetch(url)\nexcept Exception as e:\n logger.error(e)\n return None\n\n# BANNED — catch-and-ignore\ntry:\n parse(data)\nexcept Exception:\n pass\n\n# GOOD — catch what you expect\ntry:\n result = api.fetch(url)\nexcept httpx.HTTPStatusError as e:\n logger.error(\"API %d: %s\", e.response.status_code, e.request.url)\n return None\nexcept httpx.ConnectError:\n raise ServiceUnavailableError(service=\"api\") from None\n\n# GOOD — top-level boundary (only place broad catch is acceptable)\ndef main() -> int: # noqa: BROAD_EXCEPT_OK\n try:\n return run()\n except Exception:\n logger.exception(\"unhandled error\")\n return 1\n```\n\n### Async\n\n- `import asyncio` is **BANNED**. Use `import anyio`.\n- For background tasks, use `anyio.create_task_group`. Never fire-and-forget with `asyncio.create_task`.\n- For concurrency gates, use `anyio.CapacityLimiter` (not `asyncio.Semaphore`).\n- Load `async-anyio.md` when writing async code for the full pattern library.\n\n### Data modeling — which container, when\n\nAll model fields carry type annotations. No `Any`, no untyped dicts in public APIs.\nUse `polars` + `duckdb` for data. pandas is never the right answer in this stack.\n\n| Situation | Use |\n|---|---|\n| User input, API request/response | `Pydantic BaseModel (frozen=True)` |\n| Internal value object (no I/O) | `@dataclass(frozen=True, slots=True)` |\n| Function with multiple outcomes | Union of frozen dataclasses + `match` |\n| Dict shape for JSON compat / `**kwargs` | `TypedDict` |\n| Fixed constants | `StrEnum` / `IntEnum` |\n| Distinct primitive (UserId vs MovieId) | `NewType` |\n| Contract / capability | `Protocol` |\n| Contract + shared implementation | `ABC` |\n| ORM model (SQLAlchemy) | `Mapped[]` — inherently mutable, `# noqa: MUTABLE_OK` |\n| Config from env vars | `pydantic-settings BaseSettings` |\n\n**The one rule**: data crosses trust boundary → Pydantic. Everything else → dataclass.\n\nLoad `data-modeling.md` for the full decision flowchart and comparison matrix.\n\n### When frozen=True does not apply\n\n- **ORM models** — SQLAlchemy `Mapped[]` requires mutation. Use `# noqa: MUTABLE_OK`.\n- **Builder / accumulator** — object exists to be mutated (counter, buffer, state machine). Docstring must explain why.\n- **Pydantic Settings** — tests override fields. Mutable is acceptable.\n\nIf you need `# noqa: MUTABLE_OK`, the class docstring must say why mutation is required.\n\n### Libraries\n\nCanonical defaults (override only if `pyproject.toml` explicitly picks something else):\n\n| Domain | Library | Reason |\n|---|---|---|\n| CLI | `typer` | Type-annotated CLI from function sigs |\n| Pretty output | `rich` | Tables, progress, tracebacks, markdown |\n| HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) | Next-gen HTTP client (Pydantic stewardship), HTTP/2, brotli+zstd. Always `httpx2[http2,brotli,zstd]`. See `httpx2-optimization.md` |\n| Validation | `pydantic` v2 | Fast native validator, JSON Schema |\n| Web API | `fastapi` | Async, Pydantic-native, OpenAPI |\n| ORM | `sqlalchemy` 2.x async | `Mapped[]` types, async sessions |\n| DB driver (Postgres) | `asyncpg` (via SQLAlchemy) | Fastest PG driver |\n| AI agents | `pydantic-ai` | Typed deps, structured output |\n| TUI | `textual` | Rich-based, CSS layout, widgets |\n| Logging | `rich.logging.RichHandler` | Pretty; swap to `structlog` in prod |\n\n## pyproject.toml — the one true config\n\nScaffold a new project with all strict defaults pre-configured:\n\n```bash\nuv run ../../scripts/python/new-project.py myproject\nuv run ../../scripts/python/new-project.py myproject --path ./workspace\nuv run ../../scripts/python/new-project.py myproject --lib # publishable library\n```\n\nCreates via `uv init`, then injects basedpyright `typeCheckingMode = \"all\"` + ruff `select = [\"ALL\"]` + pytest strict. Cross-platform (macOS, Linux, Windows).\n\nFor manual setup: `uv init --app myproject`, then load `pyproject-strict.md`.\n\n## PEP 723 — inline script metadata (mandatory for ALL scripts)\n\nEvery `.py` script — even throwaway — MUST use PEP 723 inline metadata with the `# ─── How to run ───` comment block. No venv, no `requirements.txt`. The script IS the environment spec. A script without the usage comment block is incomplete.\n\nScaffold with: `uv run ../../scripts/python/new-script.py <name> --deps \"httpx2[http2,brotli,zstd]\"` (writes to temp dir by default, `--output` for specific path).\n\nLoad `one-liners.md` for full patterns, examples, and anti-patterns.\n\n## Reference loading\n\nLoad on demand — not all at once.\n\n| Need | Load |\n|---|---|\n| Full pyproject.toml config | `pyproject-strict.md` |\n| Type patterns (NewType, Final, enums, narrowing) | `type-patterns.md` |\n| Data modeling (container choice, frozen, parse-don't-validate) | `data-modeling.md` |\n| Error handling (typed errors, union returns, exhaustive match) | `error-handling.md` |\n| Async patterns (anyio) | `async-anyio.md` |\n| Data processing (polars / duckdb) | `data-processing.md` |\n| FastAPI + SQLAlchemy stack | `fastapi-stack.md` |\n| Library decision tree | `libraries.md` |\n| **httpx2 optimization** (MUST load for any network code) | `httpx2-optimization.md` |\n| **orjson** (when JSON is in the hot path; FastAPI/Pydantic v2 integration) | `orjson-stack.md` |\n| One-liner scripts (PEP 723) | `one-liners.md` |\n| PydanticAI agents | `pydantic-ai.md` |\n| Textual TUI | `textual-tui.md` |\n\n## httpx2 — mandatory for ALL network requests\n\nEvery outgoing HTTP call MUST use [`httpx2`](https://github.com/pydantic/httpx2) (`httpx2[http2,brotli,zstd]`). Never `requests`, never `aiohttp`, never the original `httpx`.\n\n**ALL optimizations are ON by default — not optional, not progressive, not \"nice to have\".** A bare `httpx2.AsyncClient()` is a bug — treat it like a lint violation. The correct way is the factory pattern in `httpx2-optimization.md` with: HTTP/2 enabled, tuned connection pool (200/40/30s), split timeouts (5/30/10/10), transport retries (3), TCP_NODELAY, follow_redirects, and event hooks for observability.\n\nWhen writing or reviewing ANY network code, **ALWAYS load `httpx2-optimization.md`** and use the factory pattern verbatim. No exceptions.\n\n## No-excuse audit\n\nViolations caught by `../../scripts/python/check-no-excuse-rules.py`. Run after every edit session.\n\n| Rule ID | Catches | Opt-out |\n|---|---|---|\n| `cast-any` | `cast(Any, ...)` | None — redesign types |\n| `type-ignore` | `# type: ignore` | None — fix the type |\n| `pyright-ignore` | `# pyright: ignore` | None — fix the type |\n| `bare-except` | `except:` with no class | None — name the exception |\n| `silent-except` | `except X: pass` / `except X: ...` | None — handle or re-raise |\n| `no-asyncio` | `import asyncio` | `# noqa: ANYIO_OK` |\n| `no-pandas` | `import pandas` | `# noqa: PANDAS_OK` |\n| `mutable-dataclass` | `@dataclass` without `frozen=True` | `# noqa: MUTABLE_OK` |\n| `missing-slots` | `@dataclass` without `slots=True` | `# noqa: SLOTS_OK` |\n| `raw-dict-return` | `-> dict` in function return type | `# noqa: DICT_OK` |\n| `missing-assert-never` | `match` block without `assert_never` default | `# noqa: MATCH_OK` |\n| `generic-exception` | `raise ValueError(\"...\")` / `raise TypeError(\"...\")` with bare string | `# noqa: GENERIC_ERR_OK` |\n| `no-object` | `object` used as type annotation (param, return, generic arg) | `# noqa: OBJECT_OK` |\n| `if-elif-on-variant` | `if isinstance()`/`if x == Enum.V` chain that should be `match/case` | `# noqa: IF_VARIANT_OK` |\n| `oversized-module` | File exceeds 250 pure LOC (non-blank, non-comment) | `# noqa: SIZE_OK` |\n| `broad-except` | `except Exception` / `except BaseException` (too broad) | `# noqa: BROAD_EXCEPT_OK` |\n\nFix every violation before declaring work done. basedpyright + ruff strict config catches the rest.\n\n## In tests\n\nTests are strict too, with these exceptions (already configured in `pyproject.toml` per-file-ignores):\n\n| In tests you may | Why |\n|---|---|\n| Use `assert` | That's how pytest works (`S101` ignored) |\n| Use magic numbers | Test data (`PLR2004` ignored) |\n| Access `_private` members | Testing internals (`SLF001` ignored) |\n| Skip docstrings | Test names are the docs (`D` ignored) |\n| Have unused function args | Fixtures (`ARG` ignored) |\n\nTests still follow the iron list — frozen dataclasses, typed errors, exhaustive match. If test fixtures need mutable state, use `# noqa: MUTABLE_OK` on the fixture class.\n\n## Existing codebases\n\nWhen editing an existing file that doesn't follow these rules: **write new code in strict style, don't refactor existing code in the same change.** Mixing feature work with style migration makes reviews harder and bugs likelier.\n\n## Activation\n\nThis skill activates whenever you are writing or modifying any `.py` file. Even one-off scripts get the strict treatment — that is the whole point of PEP 723 + uv: production hygiene with throwaway ergonomics.\n","exit_code":0,"duration":{"secs":0,"nanos":83719102},"formatted_output":"\n# Python Programmer\n\nModern Python. Type-strict, stack-first, async-correct.\n\n## Philosophy\n\nThe type checker is your compiler. Make illegal states unrepresentable. Parse at boundaries. Own resources explicitly. Every function has a contract; the type system enforces it.\n\n## Hard rules\n\nThese are deliberate project choices. Violations are always wrong, not \"style preferences\".\n\n### Tooling\n\n| Category | Use | Never |\n|---|---|---|\n| Package manager | `uv` | pip, poetry, conda, pipenv |\n| Type checker | `basedpyright` (`typeCheckingMode = \"all\"`) | pyright, mypy |\n| Linter + formatter | `ruff` (`select = [\"ALL\"]`) | flake8, black, isort, autopep8 |\n| Async runtime | `anyio` | `import asyncio` |\n| Data | `polars` + `duckdb` + `numpy` | pandas |\n| Web framework | FastAPI + Pydantic v2 | Flask, Django REST |\n| ORM | SQLAlchemy 2.x async | Django ORM, Tortoise |\n| HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) | requests, aiohttp, httpx |\n| Testing | `pytest` | unittest |\n| CLI | `typer` + `rich` | argparse, click, fire |\n\n### The iron list\n\n1. **Frozen by default** — `@dataclass(frozen=True, slots=True)`. Pydantic: `model_config = ConfigDict(frozen=True)`. Mutable only when mutation is the documented purpose.\n2. **NewType for distinct IDs** — `UserId = NewType(\"UserId\", int)`. Never pass raw `int` where a branded type exists.\n3. **`match` only for variants, `if` only for booleans** — **NEVER** use `if/elif/else` to discriminate on type (`isinstance`), enum value, or literal variant. `match/case` is mandatory for these — non-negotiable. **ALWAYS** end with `case unreachable: assert_never(unreachable)` — bare `case _: pass` and `case _: raise ValueError` are banned (they silently swallow new variants). `if/else` is fine only for boolean expressions, range checks, and predicate calls that aren't variant discrimination. See \"Why `if/elif` on variants is banned\" below for examples.\n4. **Protocol over ABC** — `typing.Protocol` for interfaces. ABC only when you need shared method implementation.\n5. **No raw dicts in signatures** — params and returns use `TypedDict`, `dataclass`, or Pydantic model. Internal scratch dicts are fine.\n6. **Parse, don't validate** — constructors produce typed objects or raise. Never pass unvalidated data deeper into the call stack.\n7. **Typed errors** — error types are dataclasses or exceptions with typed fields. Never `raise ValueError(\"something\")` with a bare string. Use union returns when the caller is within 1-2 call levels and must handle the outcome (repository → service). Use exceptions when the error should propagate up many layers to a boundary handler (service → HTTP handler).\n8. **Final for constants** — module-level constants use `Final`. Mutable module globals are a code smell.\n9. **Explicit None** — annotate `-> X | None`. Never return `None` from a function whose signature omits it.\n10. **Context managers for resources** — files, DB connections, HTTP clients, locks. No manual `.close()`.\n11. **No Any, no object** — both are banned as type annotations. `object` erases all structural information (zero callable attributes, zero narrowing). Use `Protocol` (structural typing), `TypeVar` (generic pass-through), explicit union (known variants), or `TypedDict` (dict shapes).\n12. **No cast** — `cast()` is banned. Redesign the types.\n13. **No type: ignore** — fix the type error. The checker is right; you are wrong.\n14. **No broad except** — `except Exception` and `except BaseException` are banned. Catch the **specific** exception you expect. A broad catch swallows bugs you need to see — `KeyError`, `AttributeError`, `TypeError` all vanish silently. If you genuinely need a catch-all at a top-level boundary (CLI entry, HTTP handler), use `# noqa: BROAD_EXCEPT_OK` and log + re-raise.\n\n### Typing and safety\n\n- `basedpyright` in `typeCheckingMode = \"all\"`. Every public function has full annotations. Internal helpers: annotate return type; parameter types may be inferred.\n- `ruff` with `select = [\"ALL\"]`. Override specific rules per project in `pyproject.toml`, never globally disable the strict baseline.\n- Every new function must have a `docstring` unless its name + signature makes it completely obvious (e.g. `def full_name(first: str, last: str) -> str:`).\n- Use `X | Y` union syntax (PEP 604), never `Union[X, Y]` or `Optional[X]`.\n\n### Why `object` is banned\n\n`object` pretends to be safe (\"it's the top type!\") but gives **zero** narrowing and **zero** attributes. Even `Any` is more honest — it admits the boundary is untyped.\n\n```python\n# BANNED\ndef process(data: object) -> object: ...\ndef store(items: list[object]) -> None: ...\nresults: dict[str, object] = {}\n\n# GOOD — Protocol for structural typing\nclass Serializable(Protocol):\n def serialize(self) -> bytes: ...\ndef process(data: Serializable) -> ProcessResult: ...\n\n# GOOD — TypeVar for generic pass-through\ndef identity[T](x: T) -> T: ...\ndef first[T](items: Sequence[T]) -> T: ...\n\n# GOOD — explicit union for known variants\ndef parse(raw: str | bytes) -> Document: ...\n```\n\n### Why `if/elif` on variants is banned\n\n`if/elif/else` chains on type, enum, or literal values lose compile-time exhaustiveness. When a new variant is added, nothing warns you. `match/case` + `assert_never` does.\n\n```python\n# BANNED — if/elif for type discrimination\nif isinstance(event, Click):\n handle_click(event.x, event.y)\nelif isinstance(event, Scroll):\n handle_scroll(event.delta)\nelse:\n raise ValueError(f\"Unknown: {event}\") # runtime bomb\n\n# BANNED — if/elif for enum discrimination\nif status == Status.PENDING:\n start_review()\nelif status == Status.ACTIVE:\n continue_processing()\nelif status == Status.CLOSED:\n archive()\n\n# BANNED — non-exhaustive match (swallows new variants)\nmatch event:\n case Click(x, y): handle_click(x, y)\n case _: pass\n\n# GOOD — exhaustive match with assert_never\nmatch event:\n case Click(x=x, y=y):\n handle_click(x, y)\n case Scroll(delta=delta):\n handle_scroll(delta)\n case unreachable:\n assert_never(unreachable)\n\n# GOOD — enum match\nmatch status:\n case Status.PENDING: start_review()\n case Status.ACTIVE: continue_processing()\n case Status.CLOSED: archive()\n case unreachable: assert_never(unreachable)\n```\n\n`if/else` is fine for boolean conditions and range checks — things that aren't variant discrimination:\n\n```python\n# FINE — boolean, not variant\nif age >= 18:\n grant_access()\nelse:\n deny_access()\n```\n\n### Why broad `except` is banned\n\n`except Exception` catches **every** non-system exception — `KeyError`, `TypeError`, `AttributeError`, `ValueError` all vanish. You lose the stack trace that would have told you exactly what went wrong. The fix is always to name the exception you expect.\n\n```python\n# BANNED — swallows bugs\ntry:\n result = api.fetch(url)\nexcept Exception as e:\n logger.error(e)\n return None\n\n# BANNED — catch-and-ignore\ntry:\n parse(data)\nexcept Exception:\n pass\n\n# GOOD — catch what you expect\ntry:\n result = api.fetch(url)\nexcept httpx.HTTPStatusError as e:\n logger.error(\"API %d: %s\", e.response.status_code, e.request.url)\n return None\nexcept httpx.ConnectError:\n raise ServiceUnavailableError(service=\"api\") from None\n\n# GOOD — top-level boundary (only place broad catch is acceptable)\ndef main() -> int: # noqa: BROAD_EXCEPT_OK\n try:\n return run()\n except Exception:\n logger.exception(\"unhandled error\")\n return 1\n```\n\n### Async\n\n- `import asyncio` is **BANNED**. Use `import anyio`.\n- For background tasks, use `anyio.create_task_group`. Never fire-and-forget with `asyncio.create_task`.\n- For concurrency gates, use `anyio.CapacityLimiter` (not `asyncio.Semaphore`).\n- Load `async-anyio.md` when writing async code for the full pattern library.\n\n### Data modeling — which container, when\n\nAll model fields carry type annotations. No `Any`, no untyped dicts in public APIs.\nUse `polars` + `duckdb` for data. pandas is never the right answer in this stack.\n\n| Situation | Use |\n|---|---|\n| User input, API request/response | `Pydantic BaseModel (frozen=True)` |\n| Internal value object (no I/O) | `@dataclass(frozen=True, slots=True)` |\n| Function with multiple outcomes | Union of frozen dataclasses + `match` |\n| Dict shape for JSON compat / `**kwargs` | `TypedDict` |\n| Fixed constants | `StrEnum` / `IntEnum` |\n| Distinct primitive (UserId vs MovieId) | `NewType` |\n| Contract / capability | `Protocol` |\n| Contract + shared implementation | `ABC` |\n| ORM model (SQLAlchemy) | `Mapped[]` — inherently mutable, `# noqa: MUTABLE_OK` |\n| Config from env vars | `pydantic-settings BaseSettings` |\n\n**The one rule**: data crosses trust boundary → Pydantic. Everything else → dataclass.\n\nLoad `data-modeling.md` for the full decision flowchart and comparison matrix.\n\n### When frozen=True does not apply\n\n- **ORM models** — SQLAlchemy `Mapped[]` requires mutation. Use `# noqa: MUTABLE_OK`.\n- **Builder / accumulator** — object exists to be mutated (counter, buffer, state machine). Docstring must explain why.\n- **Pydantic Settings** — tests override fields. Mutable is acceptable.\n\nIf you need `# noqa: MUTABLE_OK`, the class docstring must say why mutation is required.\n\n### Libraries\n\nCanonical defaults (override only if `pyproject.toml` explicitly picks something else):\n\n| Domain | Library | Reason |\n|---|---|---|\n| CLI | `typer` | Type-annotated CLI from function sigs |\n| Pretty output | `rich` | Tables, progress, tracebacks, markdown |\n| HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) | Next-gen HTTP client (Pydantic stewardship), HTTP/2, brotli+zstd. Always `httpx2[http2,brotli,zstd]`. See `httpx2-optimization.md` |\n| Validation | `pydantic` v2 | Fast native validator, JSON Schema |\n| Web API | `fastapi` | Async, Pydantic-native, OpenAPI |\n| ORM | `sqlalchemy` 2.x async | `Mapped[]` types, async sessions |\n| DB driver (Postgres) | `asyncpg` (via SQLAlchemy) | Fastest PG driver |\n| AI agents | `pydantic-ai` | Typed deps, structured output |\n| TUI | `textual` | Rich-based, CSS layout, widgets |\n| Logging | `rich.logging.RichHandler` | Pretty; swap to `structlog` in prod |\n\n## pyproject.toml — the one true config\n\nScaffold a new project with all strict defaults pre-configured:\n\n```bash\nuv run ../../scripts/python/new-project.py myproject\nuv run ../../scripts/python/new-project.py myproject --path ./workspace\nuv run ../../scripts/python/new-project.py myproject --lib # publishable library\n```\n\nCreates via `uv init`, then injects basedpyright `typeCheckingMode = \"all\"` + ruff `select = [\"ALL\"]` + pytest strict. Cross-platform (macOS, Linux, Windows).\n\nFor manual setup: `uv init --app myproject`, then load `pyproject-strict.md`.\n\n## PEP 723 — inline script metadata (mandatory for ALL scripts)\n\nEvery `.py` script — even throwaway — MUST use PEP 723 inline metadata with the `# ─── How to run ───` comment block. No venv, no `requirements.txt`. The script IS the environment spec. A script without the usage comment block is incomplete.\n\nScaffold with: `uv run ../../scripts/python/new-script.py <name> --deps \"httpx2[http2,brotli,zstd]\"` (writes to temp dir by default, `--output` for specific path).\n\nLoad `one-liners.md` for full patterns, examples, and anti-patterns.\n\n## Reference loading\n\nLoad on demand — not all at once.\n\n| Need | Load |\n|---|---|\n| Full pyproject.toml config | `pyproject-strict.md` |\n| Type patterns (NewType, Final, enums, narrowing) | `type-patterns.md` |\n| Data modeling (container choice, frozen, parse-don't-validate) | `data-modeling.md` |\n| Error handling (typed errors, union returns, exhaustive match) | `error-handling.md` |\n| Async patterns (anyio) | `async-anyio.md` |\n| Data processing (polars / duckdb) | `data-processing.md` |\n| FastAPI + SQLAlchemy stack | `fastapi-stack.md` |\n| Library decision tree | `libraries.md` |\n| **httpx2 optimization** (MUST load for any network code) | `httpx2-optimization.md` |\n| **orjson** (when JSON is in the hot path; FastAPI/Pydantic v2 integration) | `orjson-stack.md` |\n| One-liner scripts (PEP 723) | `one-liners.md` |\n| PydanticAI agents | `pydantic-ai.md` |\n| Textual TUI | `textual-tui.md` |\n\n## httpx2 — mandatory for ALL network requests\n\nEvery outgoing HTTP call MUST use [`httpx2`](https://github.com/pydantic/httpx2) (`httpx2[http2,brotli,zstd]`). Never `requests`, never `aiohttp`, never the original `httpx`.\n\n**ALL optimizations are ON by default — not optional, not progressive, not \"nice to have\".** A bare `httpx2.AsyncClient()` is a bug — treat it like a lint violation. The correct way is the factory pattern in `httpx2-optimization.md` with: HTTP/2 enabled, tuned connection pool (200/40/30s), split timeouts (5/30/10/10), transport retries (3), TCP_NODELAY, follow_redirects, and event hooks for observability.\n\nWhen writing or reviewing ANY network code, **ALWAYS load `httpx2-optimization.md`** and use the factory pattern verbatim. No exceptions.\n\n## No-excuse audit\n\nViolations caught by `../../scripts/python/check-no-excuse-rules.py`. Run after every edit session.\n\n| Rule ID | Catches | Opt-out |\n|---|---|---|\n| `cast-any` | `cast(Any, ...)` | None — redesign types |\n| `type-ignore` | `# type: ignore` | None — fix the type |\n| `pyright-ignore` | `# pyright: ignore` | None — fix the type |\n| `bare-except` | `except:` with no class | None — name the exception |\n| `silent-except` | `except X: pass` / `except X: ...` | None — handle or re-raise |\n| `no-asyncio` | `import asyncio` | `# noqa: ANYIO_OK` |\n| `no-pandas` | `import pandas` | `# noqa: PANDAS_OK` |\n| `mutable-dataclass` | `@dataclass` without `frozen=True` | `# noqa: MUTABLE_OK` |\n| `missing-slots` | `@dataclass` without `slots=True` | `# noqa: SLOTS_OK` |\n| `raw-dict-return` | `-> dict` in function return type | `# noqa: DICT_OK` |\n| `missing-assert-never` | `match` block without `assert_never` default | `# noqa: MATCH_OK` |\n| `generic-exception` | `raise ValueError(\"...\")` / `raise TypeError(\"...\")` with bare string | `# noqa: GENERIC_ERR_OK` |\n| `no-object` | `object` used as type annotation (param, return, generic arg) | `# noqa: OBJECT_OK` |\n| `if-elif-on-variant` | `if isinstance()`/`if x == Enum.V` chain that should be `match/case` | `# noqa: IF_VARIANT_OK` |\n| `oversized-module` | File exceeds 250 pure LOC (non-blank, non-comment) | `# noqa: SIZE_OK` |\n| `broad-except` | `except Exception` / `except BaseException` (too broad) | `# noqa: BROAD_EXCEPT_OK` |\n\nFix every violation before declaring work done. basedpyright + ruff strict config catches the rest.\n\n## In tests\n\nTests are strict too, with these exceptions (already configured in `pyproject.toml` per-file-ignores):\n\n| In tests you may | Why |\n|---|---|\n| Use `assert` | That's how pytest works (`S101` ignored) |\n| Use magic numbers | Test data (`PLR2004` ignored) |\n| Access `_private` members | Testing internals (`SLF001` ignored) |\n| Skip docstrings | Test names are the docs (`D` ignored) |\n| Have unused function args | Fixtures (`ARG` ignored) |\n\nTests still follow the iron list — frozen dataclasses, typed errors, exhaustive match. If test fixtures need mutable state, use `# noqa: MUTABLE_OK` on the fixture class.\n\n## Existing codebases\n\nWhen editing an existing file that doesn't follow these rules: **write new code in strict style, don't refactor existing code in the same change.** Mixing feature work with style migration makes reviews harder and bugs likelier.\n\n## Activation\n\nThis skill activates whenever you are writing or modifying any `.py` file. Even one-off scripts get the strict treatment — that is the whole point of PEP 723 + uv: production hygiene with throwaway ergonomics.\n"},"started_at_ms":1789012334829,"completed_at_ms":1789012334912}}
{"timestamp":"2026-09-10T03:52:14.931Z","ordinal":37,"type":"response_item","payload":{"type":"custom_tool_call_output","id":"ctco_01a08971-d953-71b3-868d-19ba22f48568","call_id":"call_Y26Tuf9Z4SSlMe4Tgxan84xa","output":[{"type":"input_text","text":"Script completed\nWall time 0.3 seconds\nOutput:\n"},{"type":"input_text","text":"Warning: truncated output (original token count: 3946)\nTotal output lines: 314\n\n\n# Python Programmer\n\nModern Python. Type-strict, stack-first, async-correct.\n\n## Philosophy\n\nThe type checker is your compiler. Make illegal states unrepresentable. Parse at boundaries. Own resources explicitly. Every function has a contract; the type system enforces it.\n\n## Hard rules\n\nThese are deliberate project choices. Violations are always wrong, not \"style preferences\".\n\n### Tooling\n\n| Category | Use | Never |\n|---|---|---|\n| Package manager | `uv` | pip, poetry, conda, pipenv |\n| Type checker | `basedpyright` (`typeCheckingMode = \"all\"`) | pyright, mypy |\n| Linter + formatter | `ruff` (`select = [\"ALL\"]`) | flake8, black, isort, autopep8 |\n| Async runtime | `anyio` | `import asyncio` |\n| Data | `polars` + `duckdb` + `numpy` | pandas |\n| Web framework | FastAPI + Pydantic v2 | Flask, Django REST |\n| ORM | SQLAlchemy 2.x async | Django ORM, Tortoise |\n| HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) | requests, aiohttp, httpx |\n| Testing | `pytest` | unittest |\n| CLI | `typer` + `rich` | argparse, click, fire |\n\n### The iron list\n\n1. **Frozen by default** — `@dataclass(frozen=True, slots=True)`. Pydantic: `model_config = ConfigDict(frozen=True)`. Mutable only when mutation is the documented purpose.\n2. **NewType for distinct IDs** — `UserId = NewType(\"UserId\", int)`. Never pass raw `int` where a branded type exists.\n3. **`match` only for variants, `if` only for booleans** — **NEVER** use `if/elif/else` to discriminate on type (`isinstance`), enum value, or literal variant. `match/case` is mandatory for these — non-negotiable. **ALWAYS** end with `case unreachable: assert_never(unreachable)` — bare `case _: pass` and `case _: raise ValueError` are banned (they silently swallow new variants). `if/else` is fine only for boolean expressions, range checks, and predicate calls that aren't variant discrimination. See \"Why `if/elif` on variants is banned\" below for examples.\n4. **Protocol over ABC** — `typing.Protocol` for interfaces. ABC only when you need shared method implementation.\n5. **No raw dicts in signatures** — params and returns use `TypedDict`, `dataclass`, or Pydantic model. Internal scratch dicts are fine.\n6. **Parse, don't validate** — constructors produce typed objects or raise. Never pass unvalidated data deeper into the call stack.\n7. **Typed errors** — error types are dataclasses or exceptions with typed fields. Never `raise ValueError(\"something\")` with a bare string. Use union returns when the caller is within 1-2 call levels and must handle the outcome (repository → service). Use exceptions when the error should propagate up many layers to a boundary handler (service → HTTP handler).\n8. **Final for constants** — module-level constants use `Final`. Mutable module globals are a code smell.\n9. **Explicit None** — annotate `-> X | None`. Never return `None` from a function whose signature omits it.\n10. **Context managers for resources** — files, DB connections, HTTP clients, locks. No manual `.close()`.\n11. **No Any, no object** — both are banned as type annotations. `object` erases all structural information (zero callable attributes, zero narrowing). Use `Protocol` (structural typing), `TypeVar` (generic pass-through), explicit union (known variants), or `TypedDict` (dict shapes).\n12. **No cast** — `cast()` is banned. Redesign the types.\n13. **No type: ignore** — fix the type error. The checker is right; you are wrong.\n14. **No broad except** — `except Exception` and `except BaseException` are banned. Catch the **specific** exception you expect. A broad catch swallows bugs you need to see — `KeyError`, `AttributeError`, `TypeError` all vanish silently. If you genuinely need a catch-all at a top-level boundary (CLI entry, HTTP handler), use `# noqa: BROAD_EXCEPT_OK` and log + re-raise.\n\n### Typing and safety\n\n- `basedpyright` in `typeCheckingMode = \"all\"`. Every public function has full annotations. Internal helpers: annotate return type; parameter types may be inferred.\n- `ruff` with `select = [\"ALL\"]`. Override specific rules per project in `pyproject.toml`, never globally disable the strict baseline.\n- Every new function must have a `docstring` unless its name + signature makes it completely obvious (e.g. `def full_name(first: str, last: str) -> str:`).\n- Use `X | Y` union syntax (PEP 604), never `Union[X, Y]` or `Optional[X]`.\n\n### Why `object` is banned\n\n`object` pretends to be safe (\"it's the top type!\") but gives **zero** narrowing and **zero** attributes. Even `Any` is more honest — it admits the boundary is untyped.\n\n```python\n# BANNED\ndef process(data: object) -> object: ...\ndef store(items: list[object]) -> None: ...\nresults: dict[str, object] = {}\n\n# GOOD — Protocol for structural typing\nclass Serializable(Protocol):\n def serialize(self) -> bytes: ...\ndef process(data: Serializable) -> ProcessResult: ...\n\n# GOOD — TypeVar for generic pass-through\ndef identity[T](x: T) -> T: ...\ndef first[T](items: Sequence[T]) -> T: …1446 tokens truncated…n load `pyproject-strict.md`.\n\n## PEP 723 — inline script metadata (mandatory for ALL scripts)\n\nEvery `.py` script — even throwaway — MUST use PEP 723 inline metadata with the `# ─── How to run ───` comment block. No venv, no `requirements.txt`. The script IS the environment spec. A script without the usage comment block is incomplete.\n\nScaffold with: `uv run ../../scripts/python/new-script.py <name> --deps \"httpx2[http2,brotli,zstd]\"` (writes to temp dir by default, `--output` for specific path).\n\nLoad `one-liners.md` for full patterns, examples, and anti-patterns.\n\n## Reference loading\n\nLoad on demand — not all at once.\n\n| Need | Load |\n|---|---|\n| Full pyproject.toml config | `pyproject-strict.md` |\n| Type patterns (NewType, Final, enums, narrowing) | `type-patterns.md` |\n| Data modeling (container choice, frozen, parse-don't-validate) | `data-modeling.md` |\n| Error handling (typed errors, union returns, exhaustive match) | `error-handling.md` |\n| Async patterns (anyio) | `async-anyio.md` |\n| Data processing (polars / duckdb) | `data-processing.md` |\n| FastAPI + SQLAlchemy stack | `fastapi-stack.md` |\n| Library decision tree | `libraries.md` |\n| **httpx2 optimization** (MUST load for any network code) | `httpx2-optimization.md` |\n| **orjson** (when JSON is in the hot path; FastAPI/Pydantic v2 integration) | `orjson-stack.md` |\n| One-liner scripts (PEP 723) | `one-liners.md` |\n| PydanticAI agents | `pydantic-ai.md` |\n| Textual TUI | `textual-tui.md` |\n\n## httpx2 — mandatory for ALL network requests\n\nEvery outgoing HTTP call MUST use [`httpx2`](https://github.com/pydantic/httpx2) (`httpx2[http2,brotli,zstd]`). Never `requests`, never `aiohttp`, never the original `httpx`.\n\n**ALL optimizations are ON by default — not optional, not progressive, not \"nice to have\".** A bare `httpx2.AsyncClient()` is a bug — treat it like a lint violation. The correct way is the factory pattern in `httpx2-optimization.md` with: HTTP/2 enabled, tuned connection pool (200/40/30s), split timeouts (5/30/10/10), transport retries (3), TCP_NODELAY, follow_redirects, and event hooks for observability.\n\nWhen writing or reviewing ANY network code, **ALWAYS load `httpx2-optimization.md`** and use the factory pattern verbatim. No exceptions.\n\n## No-excuse audit\n\nViolations caught by `../../scripts/python/check-no-excuse-rules.py`. Run after every edit session.\n\n| Rule ID | Catches | Opt-out |\n|---|---|---|\n| `cast-any` | `cast(Any, ...)` | None — redesign types |\n| `type-ignore` | `# type: ignore` | None — fix the type |\n| `pyright-ignore` | `# pyright: ignore` | None — fix the type |\n| `bare-except` | `except:` with no class | None — name the exception |\n| `silent-except` | `except X: pass` / `except X: ...` | None — handle or re-raise |\n| `no-asyncio` | `import asyncio` | `# noqa: ANYIO_OK` |\n| `no-pandas` | `import pandas` | `# noqa: PANDAS_OK` |\n| `mutable-dataclass` | `@dataclass` without `frozen=True` | `# noqa: MUTABLE_OK` |\n| `missing-slots` | `@dataclass` without `slots=True` | `# noqa: SLOTS_OK` |\n| `raw-dict-return` | `-> dict` in function return type | `# noqa: DICT_OK` |\n| `missing-assert-never` | `match` block without `assert_never` default | `# noqa: MATCH_OK` |\n| `generic-exception` | `raise ValueError(\"...\")` / `raise TypeError(\"...\")` with bare string | `# noqa: GENERIC_ERR_OK` |\n| `no-object` | `object` used as type annotation (param, return, generic arg) | `# noqa: OBJECT_OK` |\n| `if-elif-on-variant` | `if isinstance()`/`if x == Enum.V` chain that should be `match/case` | `# noqa: IF_VARIANT_OK` |\n| `oversized-module` | File exceeds 250 pure LOC (non-blank, non-comment) | `# noqa: SIZE_OK` |\n| `broad-except` | `except Exception` / `except BaseException` (too broad) | `# noqa: BROAD_EXCEPT_OK` |\n\nFix every violation before declaring work done. basedpyright + ruff strict config catches the rest.\n\n## In tests\n\nTests are strict too, with these exceptions (already configured in `pyproject.toml` per-file-ignores):\n\n| In tests you may | Why |\n|---|---|\n| Use `assert` | That's how pytest works (`S101` ignored) |\n| Use magic numbers | Test data (`PLR2004` ignored) |\n| Access `_private` members | Testing internals (`SLF001` ignored) |\n| Skip docstrings | Test names are the docs (`D` ignored) |\n| Have unused function args | Fixtures (`ARG` ignored) |\n\nTests still follow the iron list — frozen dataclasses, typed errors, exhaustive match. If test fixtures need mutable state, use `# noqa: MUTABLE_OK` on the fixture class.\n\n## Existing codebases\n\nWhen editing an existing file that doesn't follow these rules: **write new code in strict style, don't refactor existing code in the same change.** Mixing feature work with style migration makes reviews harder and bugs likelier.\n\n## Activation\n\nThis skill activates whenever you are writing or modifying any `.py` file. Even one-off scripts get the strict treatment — that is the whole point of PEP 723 + uv: production hygiene with throwaway ergonomics.\n"}],"internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012334.9315891}}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:52:14.931Z","ordinal":37,"type":"response_item","payload":{"type":"custom_tool_call_output","id":"ctco_01a08971-d953-71b3-868d-19ba22f48568","call_id":"call_Y26Tuf9Z4SSlMe4Tgxan84xa","output":[{"type":"input_text","text":"Script completed\nWall time 0.3 seconds\nOutput:\n"},{"type":"input_text","text":"Warning: truncated output (original token count: 3946)\nTotal output lines: 314\n\n\n# Python Programmer\n\nModern Python. Type-strict, stack-first, async-correct.\n\n## Philosophy\n\nThe type checker is your compiler. Make illegal states unrepresentable. Parse at boundaries. Own resources explicitly. Every function has a contract; the type system enforces it.\n\n## Hard rules\n\nThese are deliberate project choices. Violations are always wrong, not \"style preferences\".\n\n### Tooling\n\n| Category | Use | Never |\n|---|---|---|\n| Package manager | `uv` | pip, poetry, conda, pipenv |\n| Type checker | `basedpyright` (`typeCheckingMode = \"all\"`) | pyright, mypy |\n| Linter + formatter | `ruff` (`select = [\"ALL\"]`) | flake8, black, isort, autopep8 |\n| Async runtime | `anyio` | `import asyncio` |\n| Data | `polars` + `duckdb` + `numpy` | pandas |\n| Web framework | FastAPI + Pydantic v2 | Flask, Django REST |\n| ORM | SQLAlchemy 2.x async | Django ORM, Tortoise |\n| HTTP client | [`httpx2`](https://github.com/pydantic/httpx2) | requests, aiohttp, httpx |\n| Testing | `pytest` | unittest |\n| CLI | `typer` + `rich` | argparse, click, fire |\n\n### The iron list\n\n1. **Frozen by default** — `@dataclass(frozen=True, slots=True)`. Pydantic: `model_config = ConfigDict(frozen=True)`. Mutable only when mutation is the documented purpose.\n2. **NewType for distinct IDs** — `UserId = NewType(\"UserId\", int)`. Never pass raw `int` where a branded type exists.\n3. **`match` only for variants, `if` only for booleans** — **NEVER** use `if/elif/else` to discriminate on type (`isinstance`), enum value, or literal variant. `match/case` is mandatory for these — non-negotiable. **ALWAYS** end with `case unreachable: assert_never(unreachable)` — bare `case _: pass` and `case _: raise ValueError` are banned (they silently swallow new variants). `if/else` is fine only for boolean expressions, range checks, and predicate calls that aren't variant discrimination. See \"Why `if/elif` on variants is banned\" below for examples.\n4. **Protocol over ABC** — `typing.Protocol` for interfaces. ABC only when you need shared method implementation.\n5. **No raw dicts in signatures** — params and returns use `TypedDict`, `dataclass`, or Pydantic model. Internal scratch dicts are fine.\n6. **Parse, don't validate** — constructors produce typed objects or raise. Never pass unvalidated data deeper into the call stack.\n7. **Typed errors** — error types are dataclasses or exceptions with typed fields. Never `raise ValueError(\"something\")` with a bare string. Use union returns when the caller is within 1-2 call levels and must handle the outcome (repository → service). Use exceptions when the error should propagate up many layers to a boundary handler (service → HTTP handler).\n8. **Final for constants** — module-level constants use `Final`. Mutable module globals are a code smell.\n9. **Explicit None** — annotate `-> X | None`. Never return `None` from a function whose signature omits it.\n10. **Context managers for resources** — files, DB connections, HTTP clients, locks. No manual `.close()`.\n11. **No Any, no object** — both are banned as type annotations. `object` erases all structural information (zero callable attributes, zero narrowing). Use `Protocol` (structural typing), `TypeVar` (generic pass-through), explicit union (known variants), or `TypedDict` (dict shapes).\n12. **No cast** — `cast()` is banned. Redesign the types.\n13. **No type: ignore** — fix the type error. The checker is right; you are wrong.\n14. **No broad except** — `except Exception` and `except BaseException` are banned. Catch the **specific** exception you expect. A broad catch swallows bugs you need to see — `KeyError`, `AttributeError`, `TypeError` all vanish silently. If you genuinely need a catch-all at a top-level boundary (CLI entry, HTTP handler), use `# noqa: BROAD_EXCEPT_OK` and log + re-raise.\n\n### Typing and safety\n\n- `basedpyright` in `typeCheckingMode = \"all\"`. Every public function has full annotations. Internal helpers: annotate return type; parameter types may be inferred.\n- `ruff` with `select = [\"ALL\"]`. Override specific rules per project in `pyproject.toml`, never globally disable the strict baseline.\n- Every new function must have a `docstring` unless its name + signature makes it completely obvious (e.g. `def full_name(first: str, last: str) -> str:`).\n- Use `X | Y` union syntax (PEP 604), never `Union[X, Y]` or `Optional[X]`.\n\n### Why `object` is banned\n\n`object` pretends to be safe (\"it's the top type!\") but gives **zero** narrowing and **zero** attributes. Even `Any` is more honest — it admits the boundary is untyped.\n\n```python\n# BANNED\ndef process(data: object) -> object: ...\ndef store(items: list[object]) -> None: ...\nresults: dict[str, object] = {}\n\n# GOOD — Protocol for structural typing\nclass Serializable(Protocol):\n def serialize(self) -> bytes: ...\ndef process(data: Serializable) -> ProcessResult: ...\n\n# GOOD — TypeVar for generic pass-through\ndef identity[T](x: T) -> T: ...\ndef first[T](items: Sequence[T]) -> T: …1446 tokens truncated…n load `pyproject-strict.md`.\n\n## PEP 723 — inline script metadata (mandatory for ALL scripts)\n\nEvery `.py` script — even throwaway — MUST use PEP 723 inline metadata with the `# ─── How to run ───` comment block. No venv, no `requirements.txt`. The script IS the environment spec. A script without the usage comment block is incomplete.\n\nScaffold with: `uv run ../../scripts/python/new-script.py <name> --deps \"httpx2[http2,brotli,zstd]\"` (writes to temp dir by default, `--output` for specific path).\n\nLoad `one-liners.md` for full patterns, examples, and anti-patterns.\n\n## Reference loading\n\nLoad on demand — not all at once.\n\n| Need | Load |\n|---|---|\n| Full pyproject.toml config | `pyproject-strict.md` |\n| Type patterns (NewType, Final, enums, narrowing) | `type-patterns.md` |\n| Data modeling (container choice, frozen, parse-don't-validate) | `data-modeling.md` |\n| Error handling (typed errors, union returns, exhaustive match) | `error-handling.md` |\n| Async patterns (anyio) | `async-anyio.md` |\n| Data processing (polars / duckdb) | `data-processing.md` |\n| FastAPI + SQLAlchemy stack | `fastapi-stack.md` |\n| Library decision tree | `libraries.md` |\n| **httpx2 optimization** (MUST load for any network code) | `httpx2-optimization.md` |\n| **orjson** (when JSON is in the hot path; FastAPI/Pydantic v2 integration) | `orjson-stack.md` |\n| One-liner scripts (PEP 723) | `one-liners.md` |\n| PydanticAI agents | `pydantic-ai.md` |\n| Textual TUI | `textual-tui.md` |\n\n## httpx2 — mandatory for ALL network requests\n\nEvery outgoing HTTP call MUST use [`httpx2`](https://github.com/pydantic/httpx2) (`httpx2[http2,brotli,zstd]`). Never `requests`, never `aiohttp`, never the original `httpx`.\n\n**ALL optimizations are ON by default — not optional, not progressive, not \"nice to have\".** A bare `httpx2.AsyncClient()` is a bug — treat it like a lint violation. The correct way is the factory pattern in `httpx2-optimization.md` with: HTTP/2 enabled, tuned connection pool (200/40/30s), split timeouts (5/30/10/10), transport retries (3), TCP_NODELAY, follow_redirects, and event hooks for observability.\n\nWhen writing or reviewing ANY network code, **ALWAYS load `httpx2-optimization.md`** and use the factory pattern verbatim. No exceptions.\n\n## No-excuse audit\n\nViolations caught by `../../scripts/python/check-no-excuse-rules.py`. Run after every edit session.\n\n| Rule ID | Catches | Opt-out |\n|---|---|---|\n| `cast-any` | `cast(Any, ...)` | None — redesign types |\n| `type-ignore` | `# type: ignore` | None — fix the type |\n| `pyright-ignore` | `# pyright: ignore` | None — fix the type |\n| `bare-except` | `except:` with no class | None — name the exception |\n| `silent-except` | `except X: pass` / `except X: ...` | None — handle or re-raise |\n| `no-asyncio` | `import asyncio` | `# noqa: ANYIO_OK` |\n| `no-pandas` | `import pandas` | `# noqa: PANDAS_OK` |\n| `mutable-dataclass` | `@dataclass` without `frozen=True` | `# noqa: MUTABLE_OK` |\n| `missing-slots` | `@dataclass` without `slots=True` | `# noqa: SLOTS_OK` |\n| `raw-dict-return` | `-> dict` in function return type | `# noqa: DICT_OK` |\n| `missing-assert-never` | `match` block without `assert_never` default | `# noqa: MATCH_OK` |\n| `generic-exception` | `raise ValueError(\"...\")` / `raise TypeError(\"...\")` with bare string | `# noqa: GENERIC_ERR_OK` |\n| `no-object` | `object` used as type annotation (param, return, generic arg) | `# noqa: OBJECT_OK` |\n| `if-elif-on-variant` | `if isinstance()`/`if x == Enum.V` chain that should be `match/case` | `# noqa: IF_VARIANT_OK` |\n| `oversized-module` | File exceeds 250 pure LOC (non-blank, non-comment) | `# noqa: SIZE_OK` |\n| `broad-except` | `except Exception` / `except BaseException` (too broad) | `# noqa: BROAD_EXCEPT_OK` |\n\nFix every violation before declaring work done. basedpyright + ruff strict config catches the rest.\n\n## In tests\n\nTests are strict too, with these exceptions (already configured in `pyproject.toml` per-file-ignores):\n\n| In tests you may | Why |\n|---|---|\n| Use `assert` | That's how pytest works (`S101` ignored) |\n| Use magic numbers | Test data (`PLR2004` ignored) |\n| Access `_private` members | Testing internals (`SLF001` ignored) |\n| Skip docstrings | Test names are the docs (`D` ignored) |\n| Have unused function args | Fixtures (`ARG` ignored) |\n\nTests still follow the iron list — frozen dataclasses, typed errors, exhaustive match. If test fixtures need mutable state, use `# noqa: MUTABLE_OK` on the fixture class.\n\n## Existing codebases\n\nWhen editing an existing file that doesn't follow these rules: **write new code in strict style, don't refactor existing code in the same change.** Mixing feature work with style migration makes reviews harder and bugs likelier.\n\n## Activation\n\nThis skill activates whenever you are writing or modifying any `.py` file. Even one-off scripts get the strict treatment — that is the whole point of PEP 723 + uv: production hygiene with throwaway ergonomics.\n"}],"internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012334.9315891}}}
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单行原文 · 未格式化
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{"timestamp":"2026-09-10T03:55:11.906Z","ordinal":46,"type":"response_item","payload":{"type":"custom_tool_call","id":"ctc_088f8f5d623dbe82016aa22a1fce8c87d2b4c02ea9700dd4f4","status":"completed","call_id":"call_NLgyHm8yuEurqttR5CWGsKXI","name":"exec","input":"text(await tools.exec_command({cmd:\"cat > scripts/occupancy.py <<'PY'\\n# /// script\\n# requires-python = \\\">=3.11\\\"\\n# dependencies = []\\n# ///\\n# Run inside Blender through build_scene.py.\\n\\\"\\\"\\\"Larder, central prep and pass in the middle of evening service.\\\"\\\"\\\"\\nfrom __future__ import annotations\\nimport math\\nimport random\\nimport bpy\\nfrom geo import area, collection, cube, cyl, lathe, mesh_object, rod, sphere, text, tube, Vec3\\nfrom food import dish, leaf, pan, plate\\n\\n\\ndef towel(pos: Vec3, mats: dict[str,bpy.types.Material], width: float = .38) -> None:\\n \\\"\\\"\\\"Cotton draped over a horizontal rail, with sagging pleats and hems.\\\"\\\"\\\"\\n x,y,z=pos; verts=[]; nx=24; ny=44\\n for j in range(ny+1):\\n t=j/ny\\n yy=y+.034*math.sin(math.pi*(t-.5))\\n zz=z-.48*abs(2*t-1)**1.14\\n for i in range(nx+1):\\n u=i/nx\\n wave=math.sin(u*math.pi*7+.3)*.012+math.sin(u*math.pi*13)*.004\\n verts.append((x+(u-.5)*width,yy+wave*abs(2*t-1),zz+.015*math.sin(u*8)+.018*math.sin(u*3)*abs(2*t-1)))\\n faces=[(j*(nx+1)+i,j*(nx+1)+i+1,(j+1)*(nx+1)+i+1,(j+1)*(nx+1)+i) for j in range(ny) for i in range(nx)]\\n obj=mesh_object('Gravity draped cotton towel',verts,faces,mats['cloth'])\\n mod=obj.modifiers.new('Cotton thickness','SOLIDIFY'); mod.thickness=.0014\\n for p in obj.data.polygons: p.use_smooth=True\\n for row in (2,ny-2):\\n tube('Woven blue towel border',[verts[row*(nx+1)+i] for i in range(nx+1)],.002,mats['blue'])\\n\\n\\ndef knife(pos: Vec3, mats: dict[str,bpy.types.Material], angle: float = 0) -> None:\\n x,y,z=pos\\n vertices=[(-.025,0,0),(.025,0,0),(.028,.13,0),(-.025,.205,0),(-.028,.018,0)]\\n blade=mesh_object('Forged chef knife blade',vertices,[(0,1,2,3,4)],mats['polished'])\\n blade.location=pos; blade.rotation_euler.z=angle\\n solid=blade.modifiers.new('Blade stock thickness','SOLIDIFY'); solid.thickness=.0025\\n dx=math.sin(angle)*.060; dy=-math.cos(angle)*.060\\n h=cube('Black riveted knife handle',(x+dx,y+dy,z+.006),(.027,.115,.014),mats['rubber'],.008)\\n h.rotation_euler.z=angle\\n for offset in (-.025,-.060,-.095):\\n cyl('Knife handle rivet',(x-math.sin(angle)*offset,y+math.cos(angle)*offset,z+.014),.0035,.002,mats['polished'])\\n\\n\\ndef squeeze(pos: Vec3, mats: dict[str,bpy.types.Material], label: str) -> None:\\n x,y,z=pos\\n lathe('Soft squeeze bottle '+label,pos,[(0,0),(.031,0),(.036,.016),(.036,.157),(.030,.174),(.020,.185),(.020,.199),(0,.199)],mats['translucent'])\\n lathe('Sauce visible in bottle',(x,y,z+.007),[(0,0),(.032,0),(.032,.096),(.030,.108),(0,.108)],mats['food_yellow'] if label=='AIOLI' else mats['food_brown'])\\n lathe('Squeeze nozzle',(x,y,z+.198),[(.021,0),(.021,.011),(.008,.017),(.003,.066),(.001,.066)],mats['cream'])\\n cube('Tape bottle label',(x,y-.036,z+.091),(.056,.001,.032),mats['paper'],.001)\\n text('Bottle handwritten label',label,(x-.024,y-.037,z+.085),.010,mats['ink'])\\n\\n\\ndef build(mats: dict[str,bpy.types.Material]) -> None:\\n collection('05 | Mise en place and service')\\n rng=random.Random(20930)\\n # West larder: longitudinal arrangement leaves the inner half for working.\\n for i,(name,count,kind) in enumerate([('TOMATO | 20:15',24,'tomato'),('HERBS | 20:05',37,'herbs'),('LEMON | PM',12,'lemon'),('MUSHROOM | 19:50',7,'mushroom')]):\\n y=2.62+i*.49\\n pan((.39,y,.90),mats,(name,count,kind))\\n cube('GN masking tape label',(.39,y-.126,.968),(.24,.001,.040),mats['paper'],.001)\\n text('GN prep date '+name,name,(.277,y-.128,.958),.014,mats['ink'])\\n lid=cube('Cloudy GN lid placed askew',(.73,4.31,.916),(.31,.25,.012),mats['translucent'],.025)\\n lid.rotation_euler.z=.23\\n cube('Green salad cutting board',(.73,3.77,.914),(.38,.56,.028),mats['green'],.018)\\n for i in range(13):\\n leaf('Chopped larder herb',(.75+rng.uniform(-.11,.10),3.73+rng.uniform(-.17,.15),.933),mats['food_green'],rng.uniform(0,6.28),.023)\\n knife((.76,3.71,.935),mats,.36)\\n squeeze((.27,4.58,.9),mats,'AIOLI')\\n squeeze((.49,4.60,.9),mats,'DRESSING')\\n # Open canvas roll: stitched pockets, individual tools, loosely curled top flap.\\n roll=cube('Open canvas knife roll',(.67,2.28,.907),(.61,.31,.011),mats['cloth'],.01)\\n for i in range(5):\\n xx=.42+i*.115\\n tube('Knife roll stitched pocket',[(xx-.041,2.18,.916),(xx-.041,2.31,.916),(xx+.041,2.31,.916),(xx+.041,2.18,.916)],.0008,mats['cream'])\\n knife((xx,2.30,.923),mats,(i-2)*.035)\\n tube('Rolled canvas flap',[(.37,2.44,.922),(.49,2.45,.941),(.7,2.44,.943),(.92,2.45,.923)],.017,mats['cloth'])\\n # Centre island: bread work, vegetables, towels, dispensers and blue roll.\\n cube('Red protein cutting board',(2.62,3.32,.916),(.63,.44,.032),mats['red'],.018)\\n knife((2.47,3.23,.936),mats,-.71)\\n cube('Yellow produce cutting board',(3.40,3.28,.916),(.54,.39,.032),mats['yellow'],.017)\\n for i in range(11):\\n obj=cube('Fresh julienned carrot',(3.32+rng.uniform(-.13,.13),3.28+rng.uniform(-.09,.09),.941),(.008,.068,.007),mats['food_yellow'],.003)\\n obj.rotation_euler.z=rng.uniform(-.65,.45)\\n for i in range(4):\\n sphere('Uncut cherry tomato',(3.48+rng.uniform(-.06,.03),3.40+rng.uniform(-.025,.025),.957),(.022,.019,.022),mats['food_red'])\\n cube('End grain bread board',(4.20,3.24,.922),(.59,.42,.044),mats['wood'],.027)\\n for i in range(4):\\n sphere('Crusty sliced sourdough',(4.04+i*.063,3.25,.999),(.042,.110,.063),mats['food_brown'])\\n sphere('Sourdough airy crumb',(4.049+i*.063,3.236,1.001),(.022,.097,.053),mats['cream'])\\n for i in range(22):\\n sphere('Scattered bread crumb',(4.2+rng.uniform(-.24,.23),3.21+rng.uniform(-.18,.17),.946),(.0025,.004,.002),mats['cream'])\\n cyl('Blue roll paper towel',(3.95,3.72,1.039),.081,.277,mats['blue'])\\n cyl('Blue roll cardboard core',(3.95,3.72,1.178),.023,.004,mats['food_brown'])\\n lathe('Large mixing bowl',(2.34,3.75,.90),[(.061,0),(.070,.009),(.145,.13),(.149,.145),(.145,.150),(.140,.143),(.135,.130),(.061,.016),(0,.016)],mats['polished'])\\n rod('Mixing spoon in bowl',(2.33,3.74,1.012),(2.48,3.84,1.29),.008,mats['wood'])\\n pan((2.87,3.75,.90),mats,('Diced vegetable prep',16,'mushroom'))\\n for xx,label in [(3.34,'AIOLI'),(3.47,'JUS'),(3.59,'DRESSING')]: squeeze((xx,3.79,.90),mats,label)\\n for xx,body,material in [(4.24,'CLING FILM / 300',mats['blue']),(4.60,'FOIL / 300',mats['cream'])]:\\n cube('Catering dispenser '+body,(xx,3.78,.959),(.30,.15,.118),material,.010)\\n text('Dispenser print',body,(xx-.138,3.702,.947),.018,mats['ink'])\\n rod('Dispenser serrated cutter',(xx-.139,3.699,1.01),(xx+.139,3.699,1.01),.002,mats['polished'])\\n rod('Front prep towel rail',(2.5,2.84,.80),(3.35,2.84,.80),.012,mats['steel'])\\n for xx in (2.5,3.35): rod('Towel rail mounting',(xx,2.84,.80),(xx,2.93,.80),.009,mats['steel'])\\n towel((2.91,2.84,.82),mats,.42)\\n # A separate shoulder-height rail lets cotton occupy the vertical space.\\n rod('Larder wall cloth rail',(.13,2.47,1.61),(.13,3.04,1.61),.012,mats['steel'])\\n # Pass: ticket assembly and three genuinely shaded warm pools.\\n for xx in (5.05,7.45):\\n cyl('Pass lamp upright',(xx,2.30,1.49),.019,1.08,mats['steel'])\\n cyl('Pass post welded foot',(xx,2.30,.964),.055,.024,mats['steel'])\\n rod('Pass overhead lighting bar',(5.05,2.30,2.03),(7.45,2.30,2.03),.023,mats['steel'])\\n rod('Ticket rail backing',(5.12,2.292,1.65),(7.37,2.292,1.65),.024,mats['polished'])\\n for i,(xx,yy) in enumerate([(5.45,1.98),(6.22,2.02),(7.00,1.98)]):\\n tube('Heat lamp curved support',[(xx,2.30,2.03),(xx,2.28,2.17),(xx,yy,2.16),(xx,yy,2.04)],.011,mats['steel'])\\n lathe('Spun brass heat lamp shade',(xx,yy,1.82),[(.16,0),(.161,.008),(.14,.07),(.060,.155),(.033,.16),(.028,.19)],mats['brass'])\\n lathe('Heat lamp bright interior reflector',(xx,yy,1.823),[(.157,0),(.137,.067),(.05,.143)],mats['polished'])\\n sphere('Infrared heat bulb',(xx,yy,1.90),(.035,.035,.045),mats['lightwarm'])\\n area('Pass amber heat lamp', (xx,yy,1.83),(xx,yy,.95),45,(1,.57,.25),.20)\\n dish((xx+(.03 if i==1 else 0),yy-.14,.951),mats,i)\\n for i in range(9):\\n xx=5.28+i*.234; angle=rng.uniform(-.09,.09); length=rng.uniform(.15,.24)\\n verts=[(-.082,0,0),(.082,0,0),(.079,-.018,-length+.008),(.035,-.012,-length-.002),(-.020,-.016,-length+.006),(-.080,-.01,-length)]\\n ob=mesh_object('Curling torn order docket',verts,[(0,1,2,3,4,5)],mats['paper']); ob.location=(xx,2.266,1.646); ob.rotation_euler.y=angle\\n body=f'TABLE {12+i:02d} #{184+i}\\\\n20:{21+i:02d} {2+i%3} COV\\\\n----------------\\\\n{1+i%2} DUCK\\\\n1 CELERIAC\\\\nNO NUTS' if i in (2,6) else f'TABLE {12+i:02d} #{184+i}\\\\n20:{21+i:02d} {2+i%3} COV\\\\n----------------\\\\n2 DUCK\\\\n1 FISH\\\\nFIRE MAINS'\\n tx=text('Readable service docket',body,(xx-.069,2.245,1.613),.014,mats['ink']); tx.rotation_euler.y=angle\\n cube('Ticket clip',(xx,2.246,1.647),(.025,.02,.036),mats['darksteel'],.004)\\n for base,n in [((5.02,1.80,.95),6),((7.43,1.86,.95),8)]:\\n for j in range(n): plate('Warming plate stack',(base[0],base[1],base[2]+j*.020),mats['cream'])\\n cube('Chef pass garnish tray',(6.23,2.24,.97),(.39,.22,.040),mats['steel'],.014)\\n for i in range(19): leaf('Pass picked microgreens',(6.23+rng.uniform(-.15,.15),2.24+rng.uniform(-.08,.08),.998),mats['food_green'],rng.uniform(0,6.28),.026)\\n tube('Plating tweezers',[(6.50,2.10,.958),(6.54,2.23,.958),(6.55,2.27,.958),(6.535,2.10,.958)],.002,mats['polished'])\\n towel((7.22,1.565,.97),mats,.25)\\nPY\\npython -m py_compile scripts/food.py scripts/occupancy.py\",\"max_output_tokens\":1000}));\n","internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012388.627771}}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:55:11.906Z","ordinal":46,"type":"response_item","payload":{"type":"custom_tool_call","id":"ctc_088f8f5d623dbe82016aa22a1fce8c87d2b4c02ea9700dd4f4","status":"completed","call_id":"call_NLgyHm8yuEurqttR5CWGsKXI","name":"exec","input":"text(await tools.exec_command({cmd:\"cat > scripts/occupancy.py <<'PY'\\n# /// script\\n# requires-python = \\\">=3.11\\\"\\n# dependencies = []\\n# ///\\n# Run inside Blender through build_scene.py.\\n\\\"\\\"\\\"Larder, central prep and pass in the middle of evening service.\\\"\\\"\\\"\\nfrom __future__ import annotations\\nimport math\\nimport random\\nimport bpy\\nfrom geo import area, collection, cube, cyl, lathe, mesh_object, rod, sphere, text, tube, Vec3\\nfrom food import dish, leaf, pan, plate\\n\\n\\ndef towel(pos: Vec3, mats: dict[str,bpy.types.Material], width: float = .38) -> None:\\n \\\"\\\"\\\"Cotton draped over a horizontal rail, with sagging pleats and hems.\\\"\\\"\\\"\\n x,y,z=pos; verts=[]; nx=24; ny=44\\n for j in range(ny+1):\\n t=j/ny\\n yy=y+.034*math.sin(math.pi*(t-.5))\\n zz=z-.48*abs(2*t-1)**1.14\\n for i in range(nx+1):\\n u=i/nx\\n wave=math.sin(u*math.pi*7+.3)*.012+math.sin(u*math.pi*13)*.004\\n verts.append((x+(u-.5)*width,yy+wave*abs(2*t-1),zz+.015*math.sin(u*8)+.018*math.sin(u*3)*abs(2*t-1)))\\n faces=[(j*(nx+1)+i,j*(nx+1)+i+1,(j+1)*(nx+1)+i+1,(j+1)*(nx+1)+i) for j in range(ny) for i in range(nx)]\\n obj=mesh_object('Gravity draped cotton towel',verts,faces,mats['cloth'])\\n mod=obj.modifiers.new('Cotton thickness','SOLIDIFY'); mod.thickness=.0014\\n for p in obj.data.polygons: p.use_smooth=True\\n for row in (2,ny-2):\\n tube('Woven blue towel border',[verts[row*(nx+1)+i] for i in range(nx+1)],.002,mats['blue'])\\n\\n\\ndef knife(pos: Vec3, mats: dict[str,bpy.types.Material], angle: float = 0) -> None:\\n x,y,z=pos\\n vertices=[(-.025,0,0),(.025,0,0),(.028,.13,0),(-.025,.205,0),(-.028,.018,0)]\\n blade=mesh_object('Forged chef knife blade',vertices,[(0,1,2,3,4)],mats['polished'])\\n blade.location=pos; blade.rotation_euler.z=angle\\n solid=blade.modifiers.new('Blade stock thickness','SOLIDIFY'); solid.thickness=.0025\\n dx=math.sin(angle)*.060; dy=-math.cos(angle)*.060\\n h=cube('Black riveted knife handle',(x+dx,y+dy,z+.006),(.027,.115,.014),mats['rubber'],.008)\\n h.rotation_euler.z=angle\\n for offset in (-.025,-.060,-.095):\\n cyl('Knife handle rivet',(x-math.sin(angle)*offset,y+math.cos(angle)*offset,z+.014),.0035,.002,mats['polished'])\\n\\n\\ndef squeeze(pos: Vec3, mats: dict[str,bpy.types.Material], label: str) -> None:\\n x,y,z=pos\\n lathe('Soft squeeze bottle '+label,pos,[(0,0),(.031,0),(.036,.016),(.036,.157),(.030,.174),(.020,.185),(.020,.199),(0,.199)],mats['translucent'])\\n lathe('Sauce visible in bottle',(x,y,z+.007),[(0,0),(.032,0),(.032,.096),(.030,.108),(0,.108)],mats['food_yellow'] if label=='AIOLI' else mats['food_brown'])\\n lathe('Squeeze nozzle',(x,y,z+.198),[(.021,0),(.021,.011),(.008,.017),(.003,.066),(.001,.066)],mats['cream'])\\n cube('Tape bottle label',(x,y-.036,z+.091),(.056,.001,.032),mats['paper'],.001)\\n text('Bottle handwritten label',label,(x-.024,y-.037,z+.085),.010,mats['ink'])\\n\\n\\ndef build(mats: dict[str,bpy.types.Material]) -> None:\\n collection('05 | Mise en place and service')\\n rng=random.Random(20930)\\n # West larder: longitudinal arrangement leaves the inner half for working.\\n for i,(name,count,kind) in enumerate([('TOMATO | 20:15',24,'tomato'),('HERBS | 20:05',37,'herbs'),('LEMON | PM',12,'lemon'),('MUSHROOM | 19:50',7,'mushroom')]):\\n y=2.62+i*.49\\n pan((.39,y,.90),mats,(name,count,kind))\\n cube('GN masking tape label',(.39,y-.126,.968),(.24,.001,.040),mats['paper'],.001)\\n text('GN prep date '+name,name,(.277,y-.128,.958),.014,mats['ink'])\\n lid=cube('Cloudy GN lid placed askew',(.73,4.31,.916),(.31,.25,.012),mats['translucent'],.025)\\n lid.rotation_euler.z=.23\\n cube('Green salad cutting board',(.73,3.77,.914),(.38,.56,.028),mats['green'],.018)\\n for i in range(13):\\n leaf('Chopped larder herb',(.75+rng.uniform(-.11,.10),3.73+rng.uniform(-.17,.15),.933),mats['food_green'],rng.uniform(0,6.28),.023)\\n knife((.76,3.71,.935),mats,.36)\\n squeeze((.27,4.58,.9),mats,'AIOLI')\\n squeeze((.49,4.60,.9),mats,'DRESSING')\\n # Open canvas roll: stitched pockets, individual tools, loosely curled top flap.\\n roll=cube('Open canvas knife roll',(.67,2.28,.907),(.61,.31,.011),mats['cloth'],.01)\\n for i in range(5):\\n xx=.42+i*.115\\n tube('Knife roll stitched pocket',[(xx-.041,2.18,.916),(xx-.041,2.31,.916),(xx+.041,2.31,.916),(xx+.041,2.18,.916)],.0008,mats['cream'])\\n knife((xx,2.30,.923),mats,(i-2)*.035)\\n tube('Rolled canvas flap',[(.37,2.44,.922),(.49,2.45,.941),(.7,2.44,.943),(.92,2.45,.923)],.017,mats['cloth'])\\n # Centre island: bread work, vegetables, towels, dispensers and blue roll.\\n cube('Red protein cutting board',(2.62,3.32,.916),(.63,.44,.032),mats['red'],.018)\\n knife((2.47,3.23,.936),mats,-.71)\\n cube('Yellow produce cutting board',(3.40,3.28,.916),(.54,.39,.032),mats['yellow'],.017)\\n for i in range(11):\\n obj=cube('Fresh julienned carrot',(3.32+rng.uniform(-.13,.13),3.28+rng.uniform(-.09,.09),.941),(.008,.068,.007),mats['food_yellow'],.003)\\n obj.rotation_euler.z=rng.uniform(-.65,.45)\\n for i in range(4):\\n sphere('Uncut cherry tomato',(3.48+rng.uniform(-.06,.03),3.40+rng.uniform(-.025,.025),.957),(.022,.019,.022),mats['food_red'])\\n cube('End grain bread board',(4.20,3.24,.922),(.59,.42,.044),mats['wood'],.027)\\n for i in range(4):\\n sphere('Crusty sliced sourdough',(4.04+i*.063,3.25,.999),(.042,.110,.063),mats['food_brown'])\\n sphere('Sourdough airy crumb',(4.049+i*.063,3.236,1.001),(.022,.097,.053),mats['cream'])\\n for i in range(22):\\n sphere('Scattered bread crumb',(4.2+rng.uniform(-.24,.23),3.21+rng.uniform(-.18,.17),.946),(.0025,.004,.002),mats['cream'])\\n cyl('Blue roll paper towel',(3.95,3.72,1.039),.081,.277,mats['blue'])\\n cyl('Blue roll cardboard core',(3.95,3.72,1.178),.023,.004,mats['food_brown'])\\n lathe('Large mixing bowl',(2.34,3.75,.90),[(.061,0),(.070,.009),(.145,.13),(.149,.145),(.145,.150),(.140,.143),(.135,.130),(.061,.016),(0,.016)],mats['polished'])\\n rod('Mixing spoon in bowl',(2.33,3.74,1.012),(2.48,3.84,1.29),.008,mats['wood'])\\n pan((2.87,3.75,.90),mats,('Diced vegetable prep',16,'mushroom'))\\n for xx,label in [(3.34,'AIOLI'),(3.47,'JUS'),(3.59,'DRESSING')]: squeeze((xx,3.79,.90),mats,label)\\n for xx,body,material in [(4.24,'CLING FILM / 300',mats['blue']),(4.60,'FOIL / 300',mats['cream'])]:\\n cube('Catering dispenser '+body,(xx,3.78,.959),(.30,.15,.118),material,.010)\\n text('Dispenser print',body,(xx-.138,3.702,.947),.018,mats['ink'])\\n rod('Dispenser serrated cutter',(xx-.139,3.699,1.01),(xx+.139,3.699,1.01),.002,mats['polished'])\\n rod('Front prep towel rail',(2.5,2.84,.80),(3.35,2.84,.80),.012,mats['steel'])\\n for xx in (2.5,3.35): rod('Towel rail mounting',(xx,2.84,.80),(xx,2.93,.80),.009,mats['steel'])\\n towel((2.91,2.84,.82),mats,.42)\\n # A separate shoulder-height rail lets cotton occupy the vertical space.\\n rod('Larder wall cloth rail',(.13,2.47,1.61),(.13,3.04,1.61),.012,mats['steel'])\\n # Pass: ticket assembly and three genuinely shaded warm pools.\\n for xx in (5.05,7.45):\\n cyl('Pass lamp upright',(xx,2.30,1.49),.019,1.08,mats['steel'])\\n cyl('Pass post welded foot',(xx,2.30,.964),.055,.024,mats['steel'])\\n rod('Pass overhead lighting bar',(5.05,2.30,2.03),(7.45,2.30,2.03),.023,mats['steel'])\\n rod('Ticket rail backing',(5.12,2.292,1.65),(7.37,2.292,1.65),.024,mats['polished'])\\n for i,(xx,yy) in enumerate([(5.45,1.98),(6.22,2.02),(7.00,1.98)]):\\n tube('Heat lamp curved support',[(xx,2.30,2.03),(xx,2.28,2.17),(xx,yy,2.16),(xx,yy,2.04)],.011,mats['steel'])\\n lathe('Spun brass heat lamp shade',(xx,yy,1.82),[(.16,0),(.161,.008),(.14,.07),(.060,.155),(.033,.16),(.028,.19)],mats['brass'])\\n lathe('Heat lamp bright interior reflector',(xx,yy,1.823),[(.157,0),(.137,.067),(.05,.143)],mats['polished'])\\n sphere('Infrared heat bulb',(xx,yy,1.90),(.035,.035,.045),mats['lightwarm'])\\n area('Pass amber heat lamp', (xx,yy,1.83),(xx,yy,.95),45,(1,.57,.25),.20)\\n dish((xx+(.03 if i==1 else 0),yy-.14,.951),mats,i)\\n for i in range(9):\\n xx=5.28+i*.234; angle=rng.uniform(-.09,.09); length=rng.uniform(.15,.24)\\n verts=[(-.082,0,0),(.082,0,0),(.079,-.018,-length+.008),(.035,-.012,-length-.002),(-.020,-.016,-length+.006),(-.080,-.01,-length)]\\n ob=mesh_object('Curling torn order docket',verts,[(0,1,2,3,4,5)],mats['paper']); ob.location=(xx,2.266,1.646); ob.rotation_euler.y=angle\\n body=f'TABLE {12+i:02d} #{184+i}\\\\n20:{21+i:02d} {2+i%3} COV\\\\n----------------\\\\n{1+i%2} DUCK\\\\n1 CELERIAC\\\\nNO NUTS' if i in (2,6) else f'TABLE {12+i:02d} #{184+i}\\\\n20:{21+i:02d} {2+i%3} COV\\\\n----------------\\\\n2 DUCK\\\\n1 FISH\\\\nFIRE MAINS'\\n tx=text('Readable service docket',body,(xx-.069,2.245,1.613),.014,mats['ink']); tx.rotation_euler.y=angle\\n cube('Ticket clip',(xx,2.246,1.647),(.025,.02,.036),mats['darksteel'],.004)\\n for base,n in [((5.02,1.80,.95),6),((7.43,1.86,.95),8)]:\\n for j in range(n): plate('Warming plate stack',(base[0],base[1],base[2]+j*.020),mats['cream'])\\n cube('Chef pass garnish tray',(6.23,2.24,.97),(.39,.22,.040),mats['steel'],.014)\\n for i in range(19): leaf('Pass picked microgreens',(6.23+rng.uniform(-.15,.15),2.24+rng.uniform(-.08,.08),.998),mats['food_green'],rng.uniform(0,6.28),.026)\\n tube('Plating tweezers',[(6.50,2.10,.958),(6.54,2.23,.958),(6.55,2.27,.958),(6.535,2.10,.958)],.002,mats['polished'])\\n towel((7.22,1.565,.97),mats,.25)\\nPY\\npython -m py_compile scripts/food.py scripts/occupancy.py\",\"max_output_tokens\":1000}));\n","internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012388.627771}}}
{"timestamp":"2026-09-10T03:55:12.510Z","ordinal":48,"type":"event_msg","payload":{"type":"item_completed","thread_id":"01a08971-6519-7cf3-9399-e7f6b9686fbc","turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","item":{"type":"CommandExecution","id":"exec-275e630f-105a-4534-b4cc-ec5eeaf68e24","process_id":"52917","command":["/usr/bin/bash","-lc","cat > scripts/occupancy.py <<'PY'\n# /// script\n# requires-python = \">=3.11\"\n# dependencies = []\n# ///\n# Run inside Blender through build_scene.py.\n\"\"\"Larder, central prep and pass in the middle of evening service.\"\"\"\nfrom __future__ import annotations\nimport math\nimport random\nimport bpy\nfrom geo import area, collection, cube, cyl, lathe, mesh_object, rod, sphere, text, tube, Vec3\nfrom food import dish, leaf, pan, plate\n\n\ndef towel(pos: Vec3, mats: dict[str,bpy.types.Material], width: float = .38) -> None:\n \"\"\"Cotton draped over a horizontal rail, with sagging pleats and hems.\"\"\"\n x,y,z=pos; verts=[]; nx=24; ny=44\n for j in range(ny+1):\n t=j/ny\n yy=y+.034*math.sin(math.pi*(t-.5))\n zz=z-.48*abs(2*t-1)**1.14\n for i in range(nx+1):\n u=i/nx\n wave=math.sin(u*math.pi*7+.3)*.012+math.sin(u*math.pi*13)*.004\n verts.append((x+(u-.5)*width,yy+wave*abs(2*t-1),zz+.015*math.sin(u*8)+.018*math.sin(u*3)*abs(2*t-1)))\n faces=[(j*(nx+1)+i,j*(nx+1)+i+1,(j+1)*(nx+1)+i+1,(j+1)*(nx+1)+i) for j in range(ny) for i in range(nx)]\n obj=mesh_object('Gravity draped cotton towel',verts,faces,mats['cloth'])\n mod=obj.modifiers.new('Cotton thickness','SOLIDIFY'); mod.thickness=.0014\n for p in obj.data.polygons: p.use_smooth=True\n for row in (2,ny-2):\n tube('Woven blue towel border',[verts[row*(nx+1)+i] for i in range(nx+1)],.002,mats['blue'])\n\n\ndef knife(pos: Vec3, mats: dict[str,bpy.types.Material], angle: float = 0) -> None:\n x,y,z=pos\n vertices=[(-.025,0,0),(.025,0,0),(.028,.13,0),(-.025,.205,0),(-.028,.018,0)]\n blade=mesh_object('Forged chef knife blade',vertices,[(0,1,2,3,4)],mats['polished'])\n blade.location=pos; blade.rotation_euler.z=angle\n solid=blade.modifiers.new('Blade stock thickness','SOLIDIFY'); solid.thickness=.0025\n dx=math.sin(angle)*.060; dy=-math.cos(angle)*.060\n h=cube('Black riveted knife handle',(x+dx,y+dy,z+.006),(.027,.115,.014),mats['rubber'],.008)\n h.rotation_euler.z=angle\n for offset in (-.025,-.060,-.095):\n cyl('Knife handle rivet',(x-math.sin(angle)*offset,y+math.cos(angle)*offset,z+.014),.0035,.002,mats['polished'])\n\n\ndef squeeze(pos: Vec3, mats: dict[str,bpy.types.Material], label: str) -> None:\n x,y,z=pos\n lathe('Soft squeeze bottle '+label,pos,[(0,0),(.031,0),(.036,.016),(.036,.157),(.030,.174),(.020,.185),(.020,.199),(0,.199)],mats['translucent'])\n lathe('Sauce visible in bottle',(x,y,z+.007),[(0,0),(.032,0),(.032,.096),(.030,.108),(0,.108)],mats['food_yellow'] if label=='AIOLI' else mats['food_brown'])\n lathe('Squeeze nozzle',(x,y,z+.198),[(.021,0),(.021,.011),(.008,.017),(.003,.066),(.001,.066)],mats['cream'])\n cube('Tape bottle label',(x,y-.036,z+.091),(.056,.001,.032),mats['paper'],.001)\n text('Bottle handwritten label',label,(x-.024,y-.037,z+.085),.010,mats['ink'])\n\n\ndef build(mats: dict[str,bpy.types.Material]) -> None:\n collection('05 | Mise en place and service')\n rng=random.Random(20930)\n # West larder: longitudinal arrangement leaves the inner half for working.\n for i,(name,count,kind) in enumerate([('TOMATO | 20:15',24,'tomato'),('HERBS | 20:05',37,'herbs'),('LEMON | PM',12,'lemon'),('MUSHROOM | 19:50',7,'mushroom')]):\n y=2.62+i*.49\n pan((.39,y,.90),mats,(name,count,kind))\n cube('GN masking tape label',(.39,y-.126,.968),(.24,.001,.040),mats['paper'],.001)\n text('GN prep date '+name,name,(.277,y-.128,.958),.014,mats['ink'])\n lid=cube('Cloudy GN lid placed askew',(.73,4.31,.916),(.31,.25,.012),mats['translucent'],.025)\n lid.rotation_euler.z=.23\n cube('Green salad cutting board',(.73,3.77,.914),(.38,.56,.028),mats['green'],.018)\n for i in range(13):\n leaf('Chopped larder herb',(.75+rng.uniform(-.11,.10),3.73+rng.uniform(-.17,.15),.933),mats['food_green'],rng.uniform(0,6.28),.023)\n knife((.76,3.71,.935),mats,.36)\n squeeze((.27,4.58,.9),mats,'AIOLI')\n squeeze((.49,4.60,.9),mats,'DRESSING')\n # Open canvas roll: stitched pockets, individual tools, loosely curled top flap.\n roll=cube('Open canvas knife roll',(.67,2.28,.907),(.61,.31,.011),mats['cloth'],.01)\n for i in range(5):\n xx=.42+i*.115\n tube('Knife roll stitched pocket',[(xx-.041,2.18,.916),(xx-.041,2.31,.916),(xx+.041,2.31,.916),(xx+.041,2.18,.916)],.0008,mats['cream'])\n knife((xx,2.30,.923),mats,(i-2)*.035)\n tube('Rolled canvas flap',[(.37,2.44,.922),(.49,2.45,.941),(.7,2.44,.943),(.92,2.45,.923)],.017,mats['cloth'])\n # Centre island: bread work, vegetables, towels, dispensers and blue roll.\n cube('Red protein cutting board',(2.62,3.32,.916),(.63,.44,.032),mats['red'],.018)\n knife((2.47,3.23,.936),mats,-.71)\n cube('Yellow produce cutting board',(3.40,3.28,.916),(.54,.39,.032),mats['yellow'],.017)\n for i in range(11):\n obj=cube('Fresh julienned carrot',(3.32+rng.uniform(-.13,.13),3.28+rng.uniform(-.09,.09),.941),(.008,.068,.007),mats['food_yellow'],.003)\n obj.rotation_euler.z=rng.uniform(-.65,.45)\n for i in range(4):\n sphere('Uncut cherry tomato',(3.48+rng.uniform(-.06,.03),3.40+rng.uniform(-.025,.025),.957),(.022,.019,.022),mats['food_red'])\n cube('End grain bread board',(4.20,3.24,.922),(.59,.42,.044),mats['wood'],.027)\n for i in range(4):\n sphere('Crusty sliced sourdough',(4.04+i*.063,3.25,.999),(.042,.110,.063),mats['food_brown'])\n sphere('Sourdough airy crumb',(4.049+i*.063,3.236,1.001),(.022,.097,.053),mats['cream'])\n for i in range(22):\n sphere('Scattered bread crumb',(4.2+rng.uniform(-.24,.23),3.21+rng.uniform(-.18,.17),.946),(.0025,.004,.002),mats['cream'])\n cyl('Blue roll paper towel',(3.95,3.72,1.039),.081,.277,mats['blue'])\n cyl('Blue roll cardboard core',(3.95,3.72,1.178),.023,.004,mats['food_brown'])\n lathe('Large mixing bowl',(2.34,3.75,.90),[(.061,0),(.070,.009),(.145,.13),(.149,.145),(.145,.150),(.140,.143),(.135,.130),(.061,.016),(0,.016)],mats['polished'])\n rod('Mixing spoon in bowl',(2.33,3.74,1.012),(2.48,3.84,1.29),.008,mats['wood'])\n pan((2.87,3.75,.90),mats,('Diced vegetable prep',16,'mushroom'))\n for xx,label in [(3.34,'AIOLI'),(3.47,'JUS'),(3.59,'DRESSING')]: squeeze((xx,3.79,.90),mats,label)\n for xx,body,material in [(4.24,'CLING FILM / 300',mats['blue']),(4.60,'FOIL / 300',mats['cream'])]:\n cube('Catering dispenser '+body,(xx,3.78,.959),(.30,.15,.118),material,.010)\n text('Dispenser print',body,(xx-.138,3.702,.947),.018,mats['ink'])\n rod('Dispenser serrated cutter',(xx-.139,3.699,1.01),(xx+.139,3.699,1.01),.002,mats['polished'])\n rod('Front prep towel rail',(2.5,2.84,.80),(3.35,2.84,.80),.012,mats['steel'])\n for xx in (2.5,3.35): rod('Towel rail mounting',(xx,2.84,.80),(xx,2.93,.80),.009,mats['steel'])\n towel((2.91,2.84,.82),mats,.42)\n # A separate shoulder-height rail lets cotton occupy the vertical space.\n rod('Larder wall cloth rail',(.13,2.47,1.61),(.13,3.04,1.61),.012,mats['steel'])\n # Pass: ticket assembly and three genuinely shaded warm pools.\n for xx in (5.05,7.45):\n cyl('Pass lamp upright',(xx,2.30,1.49),.019,1.08,mats['steel'])\n cyl('Pass post welded foot',(xx,2.30,.964),.055,.024,mats['steel'])\n rod('Pass overhead lighting bar',(5.05,2.30,2.03),(7.45,2.30,2.03),.023,mats['steel'])\n rod('Ticket rail backing',(5.12,2.292,1.65),(7.37,2.292,1.65),.024,mats['polished'])\n for i,(xx,yy) in enumerate([(5.45,1.98),(6.22,2.02),(7.00,1.98)]):\n tube('Heat lamp curved support',[(xx,2.30,2.03),(xx,2.28,2.17),(xx,yy,2.16),(xx,yy,2.04)],.011,mats['steel'])\n lathe('Spun brass heat lamp shade',(xx,yy,1.82),[(.16,0),(.161,.008),(.14,.07),(.060,.155),(.033,.16),(.028,.19)],mats['brass'])\n lathe('Heat lamp bright interior reflector',(xx,yy,1.823),[(.157,0),(.137,.067),(.05,.143)],mats['polished'])\n sphere('Infrared heat bulb',(xx,yy,1.90),(.035,.035,.045),mats['lightwarm'])\n area('Pass amber heat lamp', (xx,yy,1.83),(xx,yy,.95),45,(1,.57,.25),.20)\n dish((xx+(.03 if i==1 else 0),yy-.14,.951),mats,i)\n for i in range(9):\n xx=5.28+i*.234; angle=rng.uniform(-.09,.09); length=rng.uniform(.15,.24)\n verts=[(-.082,0,0),(.082,0,0),(.079,-.018,-length+.008),(.035,-.012,-length-.002),(-.020,-.016,-length+.006),(-.080,-.01,-length)]\n ob=mesh_object('Curling torn order docket',verts,[(0,1,2,3,4,5)],mats['paper']); ob.location=(xx,2.266,1.646); ob.rotation_euler.y=angle\n body=f'TABLE {12+i:02d} #{184+i}\\n20:{21+i:02d} {2+i%3} COV\\n----------------\\n{1+i%2} DUCK\\n1 CELERIAC\\nNO NUTS' if i in (2,6) else f'TABLE {12+i:02d} #{184+i}\\n20:{21+i:02d} {2+i%3} COV\\n----------------\\n2 DUCK\\n1 FISH\\nFIRE MAINS'\n tx=text('Readable service docket',body,(xx-.069,2.245,1.613),.014,mats['ink']); tx.rotation_euler.y=angle\n cube('Ticket clip',(xx,2.246,1.647),(.025,.02,.036),mats['darksteel'],.004)\n for base,n in [((5.02,1.80,.95),6),((7.43,1.86,.95),8)]:\n for j in range(n): plate('Warming plate stack',(base[0],base[1],base[2]+j*.020),mats['cream'])\n cube('Chef pass garnish tray',(6.23,2.24,.97),(.39,.22,.040),mats['steel'],.014)\n for i in range(19): leaf('Pass picked microgreens',(6.23+rng.uniform(-.15,.15),2.24+rng.uniform(-.08,.08),.998),mats['food_green'],rng.uniform(0,6.28),.026)\n tube('Plating tweezers',[(6.50,2.10,.958),(6.54,2.23,.958),(6.55,2.27,.958),(6.535,2.10,.958)],.002,mats['polished'])\n towel((7.22,1.565,.97),mats,.25)\nPY\npython -m py_compile scripts/food.py scripts/occupancy.py"],"cwd":"file:///lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/kitchen","parsed_cmd":[{"type":"unknown","cmd":"cat > scripts/occupancy.py <<'PY'\n# /// script\n# requires-python = \">=3.11\"\n# dependencies = []\n# ///\n# Run inside Blender through build_scene.py.\n\"\"\"Larder, central prep and pass in the middle of evening service.\"\"\"\nfrom __future__ import annotations\nimport math\nimport random\nimport bpy\nfrom geo import area, collection, cube, cyl, lathe, mesh_object, rod, sphere, text, tube, Vec3\nfrom food import dish, leaf, pan, plate\n\n\ndef towel(pos: Vec3, mats: dict[str,bpy.types.Material], width: float = .38) -> None:\n \"\"\"Cotton draped over a horizontal rail, with sagging pleats and hems.\"\"\"\n x,y,z=pos; verts=[]; nx=24; ny=44\n for j in range(ny+1):\n t=j/ny\n yy=y+.034*math.sin(math.pi*(t-.5))\n zz=z-.48*abs(2*t-1)**1.14\n for i in range(nx+1):\n u=i/nx\n wave=math.sin(u*math.pi*7+.3)*.012+math.sin(u*math.pi*13)*.004\n verts.append((x+(u-.5)*width,yy+wave*abs(2*t-1),zz+.015*math.sin(u*8)+.018*math.sin(u*3)*abs(2*t-1)))\n faces=[(j*(nx+1)+i,j*(nx+1)+i+1,(j+1)*(nx+1)+i+1,(j+1)*(nx+1)+i) for j in range(ny) for i in range(nx)]\n obj=mesh_object('Gravity draped cotton towel',verts,faces,mats['cloth'])\n mod=obj.modifiers.new('Cotton thickness','SOLIDIFY'); mod.thickness=.0014\n for p in obj.data.polygons: p.use_smooth=True\n for row in (2,ny-2):\n tube('Woven blue towel border',[verts[row*(nx+1)+i] for i in range(nx+1)],.002,mats['blue'])\n\n\ndef knife(pos: Vec3, mats: dict[str,bpy.types.Material], angle: float = 0) -> None:\n x,y,z=pos\n vertices=[(-.025,0,0),(.025,0,0),(.028,.13,0),(-.025,.205,0),(-.028,.018,0)]\n blade=mesh_object('Forged chef knife blade',vertices,[(0,1,2,3,4)],mats['polished'])\n blade.location=pos; blade.rotation_euler.z=angle\n solid=blade.modifiers.new('Blade stock thickness','SOLIDIFY'); solid.thickness=.0025\n dx=math.sin(angle)*.060; dy=-math.cos(angle)*.060\n h=cube('Black riveted knife handle',(x+dx,y+dy,z+.006),(.027,.115,.014),mats['rubber'],.008)\n h.rotation_euler.z=angle\n for offset in (-.025,-.060,-.095):\n cyl('Knife handle rivet',(x-math.sin(angle)*offset,y+math.cos(angle)*offset,z+.014),.0035,.002,mats['polished'])\n\n\ndef squeeze(pos: Vec3, mats: dict[str,bpy.types.Material], label: str) -> None:\n x,y,z=pos\n lathe('Soft squeeze bottle '+label,pos,[(0,0),(.031,0),(.036,.016),(.036,.157),(.030,.174),(.020,.185),(.020,.199),(0,.199)],mats['translucent'])\n lathe('Sauce visible in bottle',(x,y,z+.007),[(0,0),(.032,0),(.032,.096),(.030,.108),(0,.108)],mats['food_yellow'] if label=='AIOLI' else mats['food_brown'])\n lathe('Squeeze nozzle',(x,y,z+.198),[(.021,0),(.021,.011),(.008,.017),(.003,.066),(.001,.066)],mats['cream'])\n cube('Tape bottle label',(x,y-.036,z+.091),(.056,.001,.032),mats['paper'],.001)\n text('Bottle handwritten label',label,(x-.024,y-.037,z+.085),.010,mats['ink'])\n\n\ndef build(mats: dict[str,bpy.types.Material]) -> None:\n collection('05 | Mise en place and service')\n rng=random.Random(20930)\n # West larder: longitudinal arrangement leaves the inner half for working.\n for i,(name,count,kind) in enumerate([('TOMATO | 20:15',24,'tomato'),('HERBS | 20:05',37,'herbs'),('LEMON | PM',12,'lemon'),('MUSHROOM | 19:50',7,'mushroom')]):\n y=2.62+i*.49\n pan((.39,y,.90),mats,(name,count,kind))\n cube('GN masking tape label',(.39,y-.126,.968),(.24,.001,.040),mats['paper'],.001)\n text('GN prep date '+name,name,(.277,y-.128,.958),.014,mats['ink'])\n lid=cube('Cloudy GN lid placed askew',(.73,4.31,.916),(.31,.25,.012),mats['translucent'],.025)\n lid.rotation_euler.z=.23\n cube('Green salad cutting board',(.73,3.77,.914),(.38,.56,.028),mats['green'],.018)\n for i in range(13):\n leaf('Chopped larder herb',(.75+rng.uniform(-.11,.10),3.73+rng.uniform(-.17,.15),.933),mats['food_green'],rng.uniform(0,6.28),.023)\n knife((.76,3.71,.935),mats,.36)\n squeeze((.27,4.58,.9),mats,'AIOLI')\n squeeze((.49,4.60,.9),mats,'DRESSING')\n # Open canvas roll: stitched pockets, individual tools, loosely curled top flap.\n roll=cube('Open canvas knife roll',(.67,2.28,.907),(.61,.31,.011),mats['cloth'],.01)\n for i in range(5):\n xx=.42+i*.115\n tube('Knife roll stitched pocket',[(xx-.041,2.18,.916),(xx-.041,2.31,.916),(xx+.041,2.31,.916),(xx+.041,2.18,.916)],.0008,mats['cream'])\n knife((xx,2.30,.923),mats,(i-2)*.035)\n tube('Rolled canvas flap',[(.37,2.44,.922),(.49,2.45,.941),(.7,2.44,.943),(.92,2.45,.923)],.017,mats['cloth'])\n # Centre island: bread work, vegetables, towels, dispensers and blue roll.\n cube('Red protein cutting board',(2.62,3.32,.916),(.63,.44,.032),mats['red'],.018)\n knife((2.47,3.23,.936),mats,-.71)\n cube('Yellow produce cutting board',(3.40,3.28,.916),(.54,.39,.032),mats['yellow'],.017)\n for i in range(11):\n obj=cube('Fresh julienned carrot',(3.32+rng.uniform(-.13,.13),3.28+rng.uniform(-.09,.09),.941),(.008,.068,.007),mats['food_yellow'],.003)\n obj.rotation_euler.z=rng.uniform(-.65,.45)\n for i in range(4):\n sphere('Uncut cherry tomato',(3.48+rng.uniform(-.06,.03),3.40+rng.uniform(-.025,.025),.957),(.022,.019,.022),mats['food_red'])\n cube('End grain bread board',(4.20,3.24,.922),(.59,.42,.044),mats['wood'],.027)\n for i in range(4):\n sphere('Crusty sliced sourdough',(4.04+i*.063,3.25,.999),(.042,.110,.063),mats['food_brown'])\n sphere('Sourdough airy crumb',(4.049+i*.063,3.236,1.001),(.022,.097,.053),mats['cream'])\n for i in range(22):\n sphere('Scattered bread crumb',(4.2+rng.uniform(-.24,.23),3.21+rng.uniform(-.18,.17),.946),(.0025,.004,.002),mats['cream'])\n cyl('Blue roll paper towel',(3.95,3.72,1.039),.081,.277,mats['blue'])\n cyl('Blue roll cardboard core',(3.95,3.72,1.178),.023,.004,mats['food_brown'])\n lathe('Large mixing bowl',(2.34,3.75,.90),[(.061,0),(.070,.009),(.145,.13),(.149,.145),(.145,.150),(.140,.143),(.135,.130),(.061,.016),(0,.016)],mats['polished'])\n rod('Mixing spoon in bowl',(2.33,3.74,1.012),(2.48,3.84,1.29),.008,mats['wood'])\n pan((2.87,3.75,.90),mats,('Diced vegetable prep',16,'mushroom'))\n for xx,label in [(3.34,'AIOLI'),(3.47,'JUS'),(3.59,'DRESSING')]: squeeze((xx,3.79,.90),mats,label)\n for xx,body,material in [(4.24,'CLING FILM / 300',mats['blue']),(4.60,'FOIL / 300',mats['cream'])]:\n cube('Catering dispenser '+body,(xx,3.78,.959),(.30,.15,.118),material,.010)\n text('Dispenser print',body,(xx-.138,3.702,.947),.018,mats['ink'])\n rod('Dispenser serrated cutter',(xx-.139,3.699,1.01),(xx+.139,3.699,1.01),.002,mats['polished'])\n rod('Front prep towel rail',(2.5,2.84,.80),(3.35,2.84,.80),.012,mats['steel'])\n for xx in (2.5,3.35): rod('Towel rail mounting',(xx,2.84,.80),(xx,2.93,.80),.009,mats['steel'])\n towel((2.91,2.84,.82),mats,.42)\n # A separate shoulder-height rail lets cotton occupy the vertical space.\n rod('Larder wall cloth rail',(.13,2.47,1.61),(.13,3.04,1.61),.012,mats['steel'])\n # Pass: ticket assembly and three genuinely shaded warm pools.\n for xx in (5.05,7.45):\n cyl('Pass lamp upright',(xx,2.30,1.49),.019,1.08,mats['steel'])\n cyl('Pass post welded foot',(xx,2.30,.964),.055,.024,mats['steel'])\n rod('Pass overhead lighting bar',(5.05,2.30,2.03),(7.45,2.30,2.03),.023,mats['steel'])\n rod('Ticket rail backing',(5.12,2.292,1.65),(7.37,2.292,1.65),.024,mats['polished'])\n for i,(xx,yy) in enumerate([(5.45,1.98),(6.22,2.02),(7.00,1.98)]):\n tube('Heat lamp curved support',[(xx,2.30,2.03),(xx,2.28,2.17),(xx,yy,2.16),(xx,yy,2.04)],.011,mats['steel'])\n lathe('Spun brass heat lamp shade',(xx,yy,1.82),[(.16,0),(.161,.008),(.14,.07),(.060,.155),(.033,.16),(.028,.19)],mats['brass'])\n lathe('Heat lamp bright interior reflector',(xx,yy,1.823),[(.157,0),(.137,.067),(.05,.143)],mats['polished'])\n sphere('Infrared heat bulb',(xx,yy,1.90),(.035,.035,.045),mats['lightwarm'])\n area('Pass amber heat lamp', (xx,yy,1.83),(xx,yy,.95),45,(1,.57,.25),.20)\n dish((xx+(.03 if i==1 else 0),yy-.14,.951),mats,i)\n for i in range(9):\n xx=5.28+i*.234; angle=rng.uniform(-.09,.09); length=rng.uniform(.15,.24)\n verts=[(-.082,0,0),(.082,0,0),(.079,-.018,-length+.008),(.035,-.012,-length-.002),(-.020,-.016,-length+.006),(-.080,-.01,-length)]\n ob=mesh_object('Curling torn order docket',verts,[(0,1,2,3,4,5)],mats['paper']); ob.location=(xx,2.266,1.646); ob.rotation_euler.y=angle\n body=f'TABLE {12+i:02d} #{184+i}\\n20:{21+i:02d} {2+i%3} COV\\n----------------\\n{1+i%2} DUCK\\n1 CELERIAC\\nNO NUTS' if i in (2,6) else f'TABLE {12+i:02d} #{184+i}\\n20:{21+i:02d} {2+i%3} COV\\n----------------\\n2 DUCK\\n1 FISH\\nFIRE MAINS'\n tx=text('Readable service docket',body,(xx-.069,2.245,1.613),.014,mats['ink']); tx.rotation_euler.y=angle\n cube('Ticket clip',(xx,2.246,1.647),(.025,.02,.036),mats['darksteel'],.004)\n for base,n in [((5.02,1.80,.95),6),((7.43,1.86,.95),8)]:\n for j in range(n): plate('Warming plate stack',(base[0],base[1],base[2]+j*.020),mats['cream'])\n cube('Chef pass garnish tray',(6.23,2.24,.97),(.39,.22,.040),mats['steel'],.014)\n for i in range(19): leaf('Pass picked microgreens',(6.23+rng.uniform(-.15,.15),2.24+rng.uniform(-.08,.08),.998),mats['food_green'],rng.uniform(0,6.28),.026)\n tube('Plating tweezers',[(6.50,2.10,.958),(6.54,2.23,.958),(6.55,2.27,.958),(6.535,2.10,.958)],.002,mats['polished'])\n towel((7.22,1.565,.97),mats,.25)\nPY\npython -m py_compile scripts/food.py scripts/occupancy.py"}],"source":"unified_exec_startup","status":"completed","stdout":"","stderr":"","aggregated_output":"","exit_code":0,"duration":{"secs":0,"nanos":363003219},"formatted_output":""},"started_at_ms":1789012512147,"completed_at_ms":1789012512510}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:55:12.510Z","ordinal":48,"type":"event_msg","payload":{"type":"item_completed","thread_id":"01a08971-6519-7cf3-9399-e7f6b9686fbc","turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","item":{"type":"CommandExecution","id":"exec-275e630f-105a-4534-b4cc-ec5eeaf68e24","process_id":"52917","command":["/usr/bin/bash","-lc","cat > scripts/occupancy.py <<'PY'\n# /// script\n# requires-python = \">=3.11\"\n# dependencies = []\n# ///\n# Run inside Blender through build_scene.py.\n\"\"\"Larder, central prep and pass in the middle of evening service.\"\"\"\nfrom __future__ import annotations\nimport math\nimport random\nimport bpy\nfrom geo import area, collection, cube, cyl, lathe, mesh_object, rod, sphere, text, tube, Vec3\nfrom food import dish, leaf, pan, plate\n\n\ndef towel(pos: Vec3, mats: dict[str,bpy.types.Material], width: float = .38) -> None:\n \"\"\"Cotton draped over a horizontal rail, with sagging pleats and hems.\"\"\"\n x,y,z=pos; verts=[]; nx=24; ny=44\n for j in range(ny+1):\n t=j/ny\n yy=y+.034*math.sin(math.pi*(t-.5))\n zz=z-.48*abs(2*t-1)**1.14\n for i in range(nx+1):\n u=i/nx\n wave=math.sin(u*math.pi*7+.3)*.012+math.sin(u*math.pi*13)*.004\n verts.append((x+(u-.5)*width,yy+wave*abs(2*t-1),zz+.015*math.sin(u*8)+.018*math.sin(u*3)*abs(2*t-1)))\n faces=[(j*(nx+1)+i,j*(nx+1)+i+1,(j+1)*(nx+1)+i+1,(j+1)*(nx+1)+i) for j in range(ny) for i in range(nx)]\n obj=mesh_object('Gravity draped cotton towel',verts,faces,mats['cloth'])\n mod=obj.modifiers.new('Cotton thickness','SOLIDIFY'); mod.thickness=.0014\n for p in obj.data.polygons: p.use_smooth=True\n for row in (2,ny-2):\n tube('Woven blue towel border',[verts[row*(nx+1)+i] for i in range(nx+1)],.002,mats['blue'])\n\n\ndef knife(pos: Vec3, mats: dict[str,bpy.types.Material], angle: float = 0) -> None:\n x,y,z=pos\n vertices=[(-.025,0,0),(.025,0,0),(.028,.13,0),(-.025,.205,0),(-.028,.018,0)]\n blade=mesh_object('Forged chef knife blade',vertices,[(0,1,2,3,4)],mats['polished'])\n blade.location=pos; blade.rotation_euler.z=angle\n solid=blade.modifiers.new('Blade stock thickness','SOLIDIFY'); solid.thickness=.0025\n dx=math.sin(angle)*.060; dy=-math.cos(angle)*.060\n h=cube('Black riveted knife handle',(x+dx,y+dy,z+.006),(.027,.115,.014),mats['rubber'],.008)\n h.rotation_euler.z=angle\n for offset in (-.025,-.060,-.095):\n cyl('Knife handle rivet',(x-math.sin(angle)*offset,y+math.cos(angle)*offset,z+.014),.0035,.002,mats['polished'])\n\n\ndef squeeze(pos: Vec3, mats: dict[str,bpy.types.Material], label: str) -> None:\n x,y,z=pos\n lathe('Soft squeeze bottle '+label,pos,[(0,0),(.031,0),(.036,.016),(.036,.157),(.030,.174),(.020,.185),(.020,.199),(0,.199)],mats['translucent'])\n lathe('Sauce visible in bottle',(x,y,z+.007),[(0,0),(.032,0),(.032,.096),(.030,.108),(0,.108)],mats['food_yellow'] if label=='AIOLI' else mats['food_brown'])\n lathe('Squeeze nozzle',(x,y,z+.198),[(.021,0),(.021,.011),(.008,.017),(.003,.066),(.001,.066)],mats['cream'])\n cube('Tape bottle label',(x,y-.036,z+.091),(.056,.001,.032),mats['paper'],.001)\n text('Bottle handwritten label',label,(x-.024,y-.037,z+.085),.010,mats['ink'])\n\n\ndef build(mats: dict[str,bpy.types.Material]) -> None:\n collection('05 | Mise en place and service')\n rng=random.Random(20930)\n # West larder: longitudinal arrangement leaves the inner half for working.\n for i,(name,count,kind) in enumerate([('TOMATO | 20:15',24,'tomato'),('HERBS | 20:05',37,'herbs'),('LEMON | PM',12,'lemon'),('MUSHROOM | 19:50',7,'mushroom')]):\n y=2.62+i*.49\n pan((.39,y,.90),mats,(name,count,kind))\n cube('GN masking tape label',(.39,y-.126,.968),(.24,.001,.040),mats['paper'],.001)\n text('GN prep date '+name,name,(.277,y-.128,.958),.014,mats['ink'])\n lid=cube('Cloudy GN lid placed askew',(.73,4.31,.916),(.31,.25,.012),mats['translucent'],.025)\n lid.rotation_euler.z=.23\n cube('Green salad cutting board',(.73,3.77,.914),(.38,.56,.028),mats['green'],.018)\n for i in range(13):\n leaf('Chopped larder herb',(.75+rng.uniform(-.11,.10),3.73+rng.uniform(-.17,.15),.933),mats['food_green'],rng.uniform(0,6.28),.023)\n knife((.76,3.71,.935),mats,.36)\n squeeze((.27,4.58,.9),mats,'AIOLI')\n squeeze((.49,4.60,.9),mats,'DRESSING')\n # Open canvas roll: stitched pockets, individual tools, loosely curled top flap.\n roll=cube('Open canvas knife roll',(.67,2.28,.907),(.61,.31,.011),mats['cloth'],.01)\n for i in range(5):\n xx=.42+i*.115\n tube('Knife roll stitched pocket',[(xx-.041,2.18,.916),(xx-.041,2.31,.916),(xx+.041,2.31,.916),(xx+.041,2.18,.916)],.0008,mats['cream'])\n knife((xx,2.30,.923),mats,(i-2)*.035)\n tube('Rolled canvas flap',[(.37,2.44,.922),(.49,2.45,.941),(.7,2.44,.943),(.92,2.45,.923)],.017,mats['cloth'])\n # Centre island: bread work, vegetables, towels, dispensers and blue roll.\n cube('Red protein cutting board',(2.62,3.32,.916),(.63,.44,.032),mats['red'],.018)\n knife((2.47,3.23,.936),mats,-.71)\n cube('Yellow produce cutting board',(3.40,3.28,.916),(.54,.39,.032),mats['yellow'],.017)\n for i in range(11):\n obj=cube('Fresh julienned carrot',(3.32+rng.uniform(-.13,.13),3.28+rng.uniform(-.09,.09),.941),(.008,.068,.007),mats['food_yellow'],.003)\n obj.rotation_euler.z=rng.uniform(-.65,.45)\n for i in range(4):\n sphere('Uncut cherry tomato',(3.48+rng.uniform(-.06,.03),3.40+rng.uniform(-.025,.025),.957),(.022,.019,.022),mats['food_red'])\n cube('End grain bread board',(4.20,3.24,.922),(.59,.42,.044),mats['wood'],.027)\n for i in range(4):\n sphere('Crusty sliced sourdough',(4.04+i*.063,3.25,.999),(.042,.110,.063),mats['food_brown'])\n sphere('Sourdough airy crumb',(4.049+i*.063,3.236,1.001),(.022,.097,.053),mats['cream'])\n for i in range(22):\n sphere('Scattered bread crumb',(4.2+rng.uniform(-.24,.23),3.21+rng.uniform(-.18,.17),.946),(.0025,.004,.002),mats['cream'])\n cyl('Blue roll paper towel',(3.95,3.72,1.039),.081,.277,mats['blue'])\n cyl('Blue roll cardboard core',(3.95,3.72,1.178),.023,.004,mats['food_brown'])\n lathe('Large mixing bowl',(2.34,3.75,.90),[(.061,0),(.070,.009),(.145,.13),(.149,.145),(.145,.150),(.140,.143),(.135,.130),(.061,.016),(0,.016)],mats['polished'])\n rod('Mixing spoon in bowl',(2.33,3.74,1.012),(2.48,3.84,1.29),.008,mats['wood'])\n pan((2.87,3.75,.90),mats,('Diced vegetable prep',16,'mushroom'))\n for xx,label in [(3.34,'AIOLI'),(3.47,'JUS'),(3.59,'DRESSING')]: squeeze((xx,3.79,.90),mats,label)\n for xx,body,material in [(4.24,'CLING FILM / 300',mats['blue']),(4.60,'FOIL / 300',mats['cream'])]:\n cube('Catering dispenser '+body,(xx,3.78,.959),(.30,.15,.118),material,.010)\n text('Dispenser print',body,(xx-.138,3.702,.947),.018,mats['ink'])\n rod('Dispenser serrated cutter',(xx-.139,3.699,1.01),(xx+.139,3.699,1.01),.002,mats['polished'])\n rod('Front prep towel rail',(2.5,2.84,.80),(3.35,2.84,.80),.012,mats['steel'])\n for xx in (2.5,3.35): rod('Towel rail mounting',(xx,2.84,.80),(xx,2.93,.80),.009,mats['steel'])\n towel((2.91,2.84,.82),mats,.42)\n # A separate shoulder-height rail lets cotton occupy the vertical space.\n rod('Larder wall cloth rail',(.13,2.47,1.61),(.13,3.04,1.61),.012,mats['steel'])\n # Pass: ticket assembly and three genuinely shaded warm pools.\n for xx in (5.05,7.45):\n cyl('Pass lamp upright',(xx,2.30,1.49),.019,1.08,mats['steel'])\n cyl('Pass post welded foot',(xx,2.30,.964),.055,.024,mats['steel'])\n rod('Pass overhead lighting bar',(5.05,2.30,2.03),(7.45,2.30,2.03),.023,mats['steel'])\n rod('Ticket rail backing',(5.12,2.292,1.65),(7.37,2.292,1.65),.024,mats['polished'])\n for i,(xx,yy) in enumerate([(5.45,1.98),(6.22,2.02),(7.00,1.98)]):\n tube('Heat lamp curved support',[(xx,2.30,2.03),(xx,2.28,2.17),(xx,yy,2.16),(xx,yy,2.04)],.011,mats['steel'])\n lathe('Spun brass heat lamp shade',(xx,yy,1.82),[(.16,0),(.161,.008),(.14,.07),(.060,.155),(.033,.16),(.028,.19)],mats['brass'])\n lathe('Heat lamp bright interior reflector',(xx,yy,1.823),[(.157,0),(.137,.067),(.05,.143)],mats['polished'])\n sphere('Infrared heat bulb',(xx,yy,1.90),(.035,.035,.045),mats['lightwarm'])\n area('Pass amber heat lamp', (xx,yy,1.83),(xx,yy,.95),45,(1,.57,.25),.20)\n dish((xx+(.03 if i==1 else 0),yy-.14,.951),mats,i)\n for i in range(9):\n xx=5.28+i*.234; angle=rng.uniform(-.09,.09); length=rng.uniform(.15,.24)\n verts=[(-.082,0,0),(.082,0,0),(.079,-.018,-length+.008),(.035,-.012,-length-.002),(-.020,-.016,-length+.006),(-.080,-.01,-length)]\n ob=mesh_object('Curling torn order docket',verts,[(0,1,2,3,4,5)],mats['paper']); ob.location=(xx,2.266,1.646); ob.rotation_euler.y=angle\n body=f'TABLE {12+i:02d} #{184+i}\\n20:{21+i:02d} {2+i%3} COV\\n----------------\\n{1+i%2} DUCK\\n1 CELERIAC\\nNO NUTS' if i in (2,6) else f'TABLE {12+i:02d} #{184+i}\\n20:{21+i:02d} {2+i%3} COV\\n----------------\\n2 DUCK\\n1 FISH\\nFIRE MAINS'\n tx=text('Readable service docket',body,(xx-.069,2.245,1.613),.014,mats['ink']); tx.rotation_euler.y=angle\n cube('Ticket clip',(xx,2.246,1.647),(.025,.02,.036),mats['darksteel'],.004)\n for base,n in [((5.02,1.80,.95),6),((7.43,1.86,.95),8)]:\n for j in range(n): plate('Warming plate stack',(base[0],base[1],base[2]+j*.020),mats['cream'])\n cube('Chef pass garnish tray',(6.23,2.24,.97),(.39,.22,.040),mats['steel'],.014)\n for i in range(19): leaf('Pass picked microgreens',(6.23+rng.uniform(-.15,.15),2.24+rng.uniform(-.08,.08),.998),mats['food_green'],rng.uniform(0,6.28),.026)\n tube('Plating tweezers',[(6.50,2.10,.958),(6.54,2.23,.958),(6.55,2.27,.958),(6.535,2.10,.958)],.002,mats['polished'])\n towel((7.22,1.565,.97),mats,.25)\nPY\npython -m py_compile scripts/food.py scripts/occupancy.py"],"cwd":"file:///lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/kitchen","parsed_cmd":[{"type":"unknown","cmd":"cat > scripts/occupancy.py <<'PY'\n# /// script\n# requires-python = \">=3.11\"\n# dependencies = []\n# ///\n# Run inside Blender through build_scene.py.\n\"\"\"Larder, central prep and pass in the middle of evening service.\"\"\"\nfrom __future__ import annotations\nimport math\nimport random\nimport bpy\nfrom geo import area, collection, cube, cyl, lathe, mesh_object, rod, sphere, text, tube, Vec3\nfrom food import dish, leaf, pan, plate\n\n\ndef towel(pos: Vec3, mats: dict[str,bpy.types.Material], width: float = .38) -> None:\n \"\"\"Cotton draped over a horizontal rail, with sagging pleats and hems.\"\"\"\n x,y,z=pos; verts=[]; nx=24; ny=44\n for j in range(ny+1):\n t=j/ny\n yy=y+.034*math.sin(math.pi*(t-.5))\n zz=z-.48*abs(2*t-1)**1.14\n for i in range(nx+1):\n u=i/nx\n wave=math.sin(u*math.pi*7+.3)*.012+math.sin(u*math.pi*13)*.004\n verts.append((x+(u-.5)*width,yy+wave*abs(2*t-1),zz+.015*math.sin(u*8)+.018*math.sin(u*3)*abs(2*t-1)))\n faces=[(j*(nx+1)+i,j*(nx+1)+i+1,(j+1)*(nx+1)+i+1,(j+1)*(nx+1)+i) for j in range(ny) for i in range(nx)]\n obj=mesh_object('Gravity draped cotton towel',verts,faces,mats['cloth'])\n mod=obj.modifiers.new('Cotton thickness','SOLIDIFY'); mod.thickness=.0014\n for p in obj.data.polygons: p.use_smooth=True\n for row in (2,ny-2):\n tube('Woven blue towel border',[verts[row*(nx+1)+i] for i in range(nx+1)],.002,mats['blue'])\n\n\ndef knife(pos: Vec3, mats: dict[str,bpy.types.Material], angle: float = 0) -> None:\n x,y,z=pos\n vertices=[(-.025,0,0),(.025,0,0),(.028,.13,0),(-.025,.205,0),(-.028,.018,0)]\n blade=mesh_object('Forged chef knife blade',vertices,[(0,1,2,3,4)],mats['polished'])\n blade.location=pos; blade.rotation_euler.z=angle\n solid=blade.modifiers.new('Blade stock thickness','SOLIDIFY'); solid.thickness=.0025\n dx=math.sin(angle)*.060; dy=-math.cos(angle)*.060\n h=cube('Black riveted knife handle',(x+dx,y+dy,z+.006),(.027,.115,.014),mats['rubber'],.008)\n h.rotation_euler.z=angle\n for offset in (-.025,-.060,-.095):\n cyl('Knife handle rivet',(x-math.sin(angle)*offset,y+math.cos(angle)*offset,z+.014),.0035,.002,mats['polished'])\n\n\ndef squeeze(pos: Vec3, mats: dict[str,bpy.types.Material], label: str) -> None:\n x,y,z=pos\n lathe('Soft squeeze bottle '+label,pos,[(0,0),(.031,0),(.036,.016),(.036,.157),(.030,.174),(.020,.185),(.020,.199),(0,.199)],mats['translucent'])\n lathe('Sauce visible in bottle',(x,y,z+.007),[(0,0),(.032,0),(.032,.096),(.030,.108),(0,.108)],mats['food_yellow'] if label=='AIOLI' else mats['food_brown'])\n lathe('Squeeze nozzle',(x,y,z+.198),[(.021,0),(.021,.011),(.008,.017),(.003,.066),(.001,.066)],mats['cream'])\n cube('Tape bottle label',(x,y-.036,z+.091),(.056,.001,.032),mats['paper'],.001)\n text('Bottle handwritten label',label,(x-.024,y-.037,z+.085),.010,mats['ink'])\n\n\ndef build(mats: dict[str,bpy.types.Material]) -> None:\n collection('05 | Mise en place and service')\n rng=random.Random(20930)\n # West larder: longitudinal arrangement leaves the inner half for working.\n for i,(name,count,kind) in enumerate([('TOMATO | 20:15',24,'tomato'),('HERBS | 20:05',37,'herbs'),('LEMON | PM',12,'lemon'),('MUSHROOM | 19:50',7,'mushroom')]):\n y=2.62+i*.49\n pan((.39,y,.90),mats,(name,count,kind))\n cube('GN masking tape label',(.39,y-.126,.968),(.24,.001,.040),mats['paper'],.001)\n text('GN prep date '+name,name,(.277,y-.128,.958),.014,mats['ink'])\n lid=cube('Cloudy GN lid placed askew',(.73,4.31,.916),(.31,.25,.012),mats['translucent'],.025)\n lid.rotation_euler.z=.23\n cube('Green salad cutting board',(.73,3.77,.914),(.38,.56,.028),mats['green'],.018)\n for i in range(13):\n leaf('Chopped larder herb',(.75+rng.uniform(-.11,.10),3.73+rng.uniform(-.17,.15),.933),mats['food_green'],rng.uniform(0,6.28),.023)\n knife((.76,3.71,.935),mats,.36)\n squeeze((.27,4.58,.9),mats,'AIOLI')\n squeeze((.49,4.60,.9),mats,'DRESSING')\n # Open canvas roll: stitched pockets, individual tools, loosely curled top flap.\n roll=cube('Open canvas knife roll',(.67,2.28,.907),(.61,.31,.011),mats['cloth'],.01)\n for i in range(5):\n xx=.42+i*.115\n tube('Knife roll stitched pocket',[(xx-.041,2.18,.916),(xx-.041,2.31,.916),(xx+.041,2.31,.916),(xx+.041,2.18,.916)],.0008,mats['cream'])\n knife((xx,2.30,.923),mats,(i-2)*.035)\n tube('Rolled canvas flap',[(.37,2.44,.922),(.49,2.45,.941),(.7,2.44,.943),(.92,2.45,.923)],.017,mats['cloth'])\n # Centre island: bread work, vegetables, towels, dispensers and blue roll.\n cube('Red protein cutting board',(2.62,3.32,.916),(.63,.44,.032),mats['red'],.018)\n knife((2.47,3.23,.936),mats,-.71)\n cube('Yellow produce cutting board',(3.40,3.28,.916),(.54,.39,.032),mats['yellow'],.017)\n for i in range(11):\n obj=cube('Fresh julienned carrot',(3.32+rng.uniform(-.13,.13),3.28+rng.uniform(-.09,.09),.941),(.008,.068,.007),mats['food_yellow'],.003)\n obj.rotation_euler.z=rng.uniform(-.65,.45)\n for i in range(4):\n sphere('Uncut cherry tomato',(3.48+rng.uniform(-.06,.03),3.40+rng.uniform(-.025,.025),.957),(.022,.019,.022),mats['food_red'])\n cube('End grain bread board',(4.20,3.24,.922),(.59,.42,.044),mats['wood'],.027)\n for i in range(4):\n sphere('Crusty sliced sourdough',(4.04+i*.063,3.25,.999),(.042,.110,.063),mats['food_brown'])\n sphere('Sourdough airy crumb',(4.049+i*.063,3.236,1.001),(.022,.097,.053),mats['cream'])\n for i in range(22):\n sphere('Scattered bread crumb',(4.2+rng.uniform(-.24,.23),3.21+rng.uniform(-.18,.17),.946),(.0025,.004,.002),mats['cream'])\n cyl('Blue roll paper towel',(3.95,3.72,1.039),.081,.277,mats['blue'])\n cyl('Blue roll cardboard core',(3.95,3.72,1.178),.023,.004,mats['food_brown'])\n lathe('Large mixing bowl',(2.34,3.75,.90),[(.061,0),(.070,.009),(.145,.13),(.149,.145),(.145,.150),(.140,.143),(.135,.130),(.061,.016),(0,.016)],mats['polished'])\n rod('Mixing spoon in bowl',(2.33,3.74,1.012),(2.48,3.84,1.29),.008,mats['wood'])\n pan((2.87,3.75,.90),mats,('Diced vegetable prep',16,'mushroom'))\n for xx,label in [(3.34,'AIOLI'),(3.47,'JUS'),(3.59,'DRESSING')]: squeeze((xx,3.79,.90),mats,label)\n for xx,body,material in [(4.24,'CLING FILM / 300',mats['blue']),(4.60,'FOIL / 300',mats['cream'])]:\n cube('Catering dispenser '+body,(xx,3.78,.959),(.30,.15,.118),material,.010)\n text('Dispenser print',body,(xx-.138,3.702,.947),.018,mats['ink'])\n rod('Dispenser serrated cutter',(xx-.139,3.699,1.01),(xx+.139,3.699,1.01),.002,mats['polished'])\n rod('Front prep towel rail',(2.5,2.84,.80),(3.35,2.84,.80),.012,mats['steel'])\n for xx in (2.5,3.35): rod('Towel rail mounting',(xx,2.84,.80),(xx,2.93,.80),.009,mats['steel'])\n towel((2.91,2.84,.82),mats,.42)\n # A separate shoulder-height rail lets cotton occupy the vertical space.\n rod('Larder wall cloth rail',(.13,2.47,1.61),(.13,3.04,1.61),.012,mats['steel'])\n # Pass: ticket assembly and three genuinely shaded warm pools.\n for xx in (5.05,7.45):\n cyl('Pass lamp upright',(xx,2.30,1.49),.019,1.08,mats['steel'])\n cyl('Pass post welded foot',(xx,2.30,.964),.055,.024,mats['steel'])\n rod('Pass overhead lighting bar',(5.05,2.30,2.03),(7.45,2.30,2.03),.023,mats['steel'])\n rod('Ticket rail backing',(5.12,2.292,1.65),(7.37,2.292,1.65),.024,mats['polished'])\n for i,(xx,yy) in enumerate([(5.45,1.98),(6.22,2.02),(7.00,1.98)]):\n tube('Heat lamp curved support',[(xx,2.30,2.03),(xx,2.28,2.17),(xx,yy,2.16),(xx,yy,2.04)],.011,mats['steel'])\n lathe('Spun brass heat lamp shade',(xx,yy,1.82),[(.16,0),(.161,.008),(.14,.07),(.060,.155),(.033,.16),(.028,.19)],mats['brass'])\n lathe('Heat lamp bright interior reflector',(xx,yy,1.823),[(.157,0),(.137,.067),(.05,.143)],mats['polished'])\n sphere('Infrared heat bulb',(xx,yy,1.90),(.035,.035,.045),mats['lightwarm'])\n area('Pass amber heat lamp', (xx,yy,1.83),(xx,yy,.95),45,(1,.57,.25),.20)\n dish((xx+(.03 if i==1 else 0),yy-.14,.951),mats,i)\n for i in range(9):\n xx=5.28+i*.234; angle=rng.uniform(-.09,.09); length=rng.uniform(.15,.24)\n verts=[(-.082,0,0),(.082,0,0),(.079,-.018,-length+.008),(.035,-.012,-length-.002),(-.020,-.016,-length+.006),(-.080,-.01,-length)]\n ob=mesh_object('Curling torn order docket',verts,[(0,1,2,3,4,5)],mats['paper']); ob.location=(xx,2.266,1.646); ob.rotation_euler.y=angle\n body=f'TABLE {12+i:02d} #{184+i}\\n20:{21+i:02d} {2+i%3} COV\\n----------------\\n{1+i%2} DUCK\\n1 CELERIAC\\nNO NUTS' if i in (2,6) else f'TABLE {12+i:02d} #{184+i}\\n20:{21+i:02d} {2+i%3} COV\\n----------------\\n2 DUCK\\n1 FISH\\nFIRE MAINS'\n tx=text('Readable service docket',body,(xx-.069,2.245,1.613),.014,mats['ink']); tx.rotation_euler.y=angle\n cube('Ticket clip',(xx,2.246,1.647),(.025,.02,.036),mats['darksteel'],.004)\n for base,n in [((5.02,1.80,.95),6),((7.43,1.86,.95),8)]:\n for j in range(n): plate('Warming plate stack',(base[0],base[1],base[2]+j*.020),mats['cream'])\n cube('Chef pass garnish tray',(6.23,2.24,.97),(.39,.22,.040),mats['steel'],.014)\n for i in range(19): leaf('Pass picked microgreens',(6.23+rng.uniform(-.15,.15),2.24+rng.uniform(-.08,.08),.998),mats['food_green'],rng.uniform(0,6.28),.026)\n tube('Plating tweezers',[(6.50,2.10,.958),(6.54,2.23,.958),(6.55,2.27,.958),(6.535,2.10,.958)],.002,mats['polished'])\n towel((7.22,1.565,.97),mats,.25)\nPY\npython -m py_compile scripts/food.py scripts/occupancy.py"}],"source":"unified_exec_startup","status":"completed","stdout":"","stderr":"","aggregated_output":"","exit_code":0,"duration":{"secs":0,"nanos":363003219},"formatted_output":""},"started_at_ms":1789012512147,"completed_at_ms":1789012512510}}
{"timestamp":"2026-09-10T03:55:12.556Z","ordinal":49,"type":"response_item","payload":{"type":"custom_tool_call_output","id":"ctco_01a08974-8f2c-79d3-8f6c-d321d13110fb","call_id":"call_NLgyHm8yuEurqttR5CWGsKXI","output":[{"type":"input_text","text":"Script completed\nWall time 0.6 seconds\nOutput:\n"},{"type":"input_text","text":"{\"chunk_id\":\"b0aedd\",\"wall_time_seconds\":0.36302109,\"exit_code\":0,\"original_token_count\":0,\"output\":\"\"}"}],"internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012512.556188}}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:55:12.556Z","ordinal":49,"type":"response_item","payload":{"type":"custom_tool_call_output","id":"ctco_01a08974-8f2c-79d3-8f6c-d321d13110fb","call_id":"call_NLgyHm8yuEurqttR5CWGsKXI","output":[{"type":"input_text","text":"Script completed\nWall time 0.6 seconds\nOutput:\n"},{"type":"input_text","text":"{\"chunk_id\":\"b0aedd\",\"wall_time_seconds\":0.36302109,\"exit_code\":0,\"original_token_count\":0,\"output\":\"\"}"}],"internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012512.556188}}}
{"timestamp":"2026-09-10T03:56:16.746Z","ordinal":60,"type":"event_msg","payload":{"type":"item_completed","thread_id":"01a08971-6519-7cf3-9399-e7f6b9686fbc","turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","item":{"type":"AgentMessage","id":"msg_088f8f5d623dbe82016aa22a60a63c87d29d498759e70288e9","content":[{"type":"Text","text":"The pass now has three plated orders under heat lamps, with nine individually spaced dockets and two unequal plate stacks. I’m checking the construction in Blender and correcting towel supports so the cloth does not pass through bench fronts."}],"phase":"commentary"},"started_at_ms":1789012576746,"completed_at_ms":1789012576746}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:56:16.746Z","ordinal":60,"type":"event_msg","payload":{"type":"item_completed","thread_id":"01a08971-6519-7cf3-9399-e7f6b9686fbc","turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","item":{"type":"AgentMessage","id":"msg_088f8f5d623dbe82016aa22a60a63c87d29d498759e70288e9","content":[{"type":"Text","text":"The pass now has three plated orders under heat lamps, with nine individually spaced dockets and two unequal plate stacks. I’m checking the construction in Blender and correcting towel supports so the cloth does not pass through bench fronts."}],"phase":"commentary"},"started_at_ms":1789012576746,"completed_at_ms":1789012576746}}
{"timestamp":"2026-09-10T03:56:16.756Z","ordinal":61,"type":"response_item","payload":{"type":"message","id":"msg_088f8f5d623dbe82016aa22a60a63c87d29d498759e70288e9","role":"assistant","content":[{"type":"output_text","text":"The pass now has three plated orders under heat lamps, with nine individually spaced dockets and two unequal plate stacks. I’m checking the construction in Blender and correcting towel supports so the cloth does not pass through bench fronts."}],"phase":"commentary","internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012541.204526,"content_item_kinds":["unknown"]}}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:56:16.756Z","ordinal":61,"type":"response_item","payload":{"type":"message","id":"msg_088f8f5d623dbe82016aa22a60a63c87d29d498759e70288e9","role":"assistant","content":[{"type":"output_text","text":"The pass now has three plated orders under heat lamps, with nine individually spaced dockets and two unequal plate stacks. I’m checking the construction in Blender and correcting towel supports so the cloth does not pass through bench fronts."}],"phase":"commentary","internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012541.204526,"content_item_kinds":["unknown"]}}}
{"timestamp":"2026-09-10T03:56:16.761Z","ordinal":62,"type":"response_item","payload":{"type":"custom_tool_call","id":"ctc_088f8f5d623dbe82016aa22a60a7dc87d2888edecc4519164b","status":"completed","call_id":"call_74x1tilnVSiWPueCsRMinXBi","name":"exec","input":"text(await tools.exec_command({cmd:\"python - <<'PY'\\nfrom pathlib import Path\\np=Path('scripts/occupancy.py')\\ns=p.read_text().replace(\\\"rod('Larder wall cloth rail',(.13,2.47,1.61),(.13,3.04,1.61),.012,mats['steel'])\\\", \\\"rod('Larder shoulder height cloth rail',(.14,4.77,1.61),(.97,4.77,1.61),.012,mats['steel'])\\\\n for xx in (.14,.97): rod('Larder towel rail upright',(xx,4.77,.90),(xx,4.77,1.61),.009,mats['steel'])\\\\n towel((.57,4.77,1.63),mats,.35)\\\")\\ns=s.replace(\\\"towel((7.22,1.565,.97),mats,.25)\\\",\\\"rod('Pass front towel rail',(7.0,1.52,.86),(7.45,1.52,.86),.012,mats['steel'])\\\\n for xx in (7.0,7.45): rod('Pass towel rail standoff',(xx,1.52,.86),(xx,1.595,.86),.009,mats['steel'])\\\\n towel((7.22,1.52,.88),mats,.25)\\\")\\np.write_text(s)\\np=Path('scripts/food.py');s=p.read_text().replace(\\\"(.078,.005),(.083,.005)\\\",\\\"(.078,0),(.083,0)\\\");p.write_text(s)\\nPY\\n/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/blender-4.5.13-linux-x64/blender -b --python-expr \\\"import sys; sys.path.insert(0,'scripts'); import bpy,occupancy; names='steel polished heatsteel darksteel rubber white cream black red green yellow blue translucent glass wood cloth paper ink brass lightwarm lightcool food_red food_green food_yellow food_brown'.split(); mats={n:bpy.data.materials.new(n) for n in names}; occupancy.build(mats); print('OCCUPANCY_BUILD_OK',len(bpy.data.objects))\\\"\",\"yield_time_ms\":1000,\"max_output_tokens\":2000}));\n","internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012541.204526}}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:56:16.761Z","ordinal":62,"type":"response_item","payload":{"type":"custom_tool_call","id":"ctc_088f8f5d623dbe82016aa22a60a7dc87d2888edecc4519164b","status":"completed","call_id":"call_74x1tilnVSiWPueCsRMinXBi","name":"exec","input":"text(await tools.exec_command({cmd:\"python - <<'PY'\\nfrom pathlib import Path\\np=Path('scripts/occupancy.py')\\ns=p.read_text().replace(\\\"rod('Larder wall cloth rail',(.13,2.47,1.61),(.13,3.04,1.61),.012,mats['steel'])\\\", \\\"rod('Larder shoulder height cloth rail',(.14,4.77,1.61),(.97,4.77,1.61),.012,mats['steel'])\\\\n for xx in (.14,.97): rod('Larder towel rail upright',(xx,4.77,.90),(xx,4.77,1.61),.009,mats['steel'])\\\\n towel((.57,4.77,1.63),mats,.35)\\\")\\ns=s.replace(\\\"towel((7.22,1.565,.97),mats,.25)\\\",\\\"rod('Pass front towel rail',(7.0,1.52,.86),(7.45,1.52,.86),.012,mats['steel'])\\\\n for xx in (7.0,7.45): rod('Pass towel rail standoff',(xx,1.52,.86),(xx,1.595,.86),.009,mats['steel'])\\\\n towel((7.22,1.52,.88),mats,.25)\\\")\\np.write_text(s)\\np=Path('scripts/food.py');s=p.read_text().replace(\\\"(.078,.005),(.083,.005)\\\",\\\"(.078,0),(.083,0)\\\");p.write_text(s)\\nPY\\n/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/blender-4.5.13-linux-x64/blender -b --python-expr \\\"import sys; sys.path.insert(0,'scripts'); import bpy,occupancy; names='steel polished heatsteel darksteel rubber white cream black red green yellow blue translucent glass wood cloth paper ink brass lightwarm lightcool food_red food_green food_yellow food_brown'.split(); mats={n:bpy.data.materials.new(n) for n in names}; occupancy.build(mats); print('OCCUPANCY_BUILD_OK',len(bpy.data.objects))\\\"\",\"yield_time_ms\":1000,\"max_output_tokens\":2000}));\n","internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012541.204526}}}
{"timestamp":"2026-09-10T03:56:17.967Z","ordinal":64,"type":"response_item","payload":{"type":"custom_tool_call_output","id":"ctco_01a08975-8eaf-73e3-85a3-0a55958758dc","call_id":"call_74x1tilnVSiWPueCsRMinXBi","output":[{"type":"input_text","text":"Script completed\nWall time 1.2 seconds\nOutput:\n"},{"type":"input_text","text":"{\"chunk_id\":\"e6bc68\",\"wall_time_seconds\":1.000575618,\"session_id\":6733,\"original_token_count\":0,\"output\":\"\"}"}],"internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012577.9670725}}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:56:17.967Z","ordinal":64,"type":"response_item","payload":{"type":"custom_tool_call_output","id":"ctco_01a08975-8eaf-73e3-85a3-0a55958758dc","call_id":"call_74x1tilnVSiWPueCsRMinXBi","output":[{"type":"input_text","text":"Script completed\nWall time 1.2 seconds\nOutput:\n"},{"type":"input_text","text":"{\"chunk_id\":\"e6bc68\",\"wall_time_seconds\":1.000575618,\"session_id\":6733,\"original_token_count\":0,\"output\":\"\"}"}],"internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012577.9670725}}}
{"timestamp":"2026-09-10T03:56:29.725Z","ordinal":70,"type":"event_msg","payload":{"type":"item_completed","thread_id":"01a08971-6519-7cf3-9399-e7f6b9686fbc","turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","item":{"type":"CommandExecution","id":"exec-97067288-69dd-44a9-bea6-27af6171bc5a","process_id":"6733","command":["/usr/bin/bash","-lc","python - <<'PY'\nfrom pathlib import Path\np=Path('scripts/occupancy.py')\ns=p.read_text().replace(\"rod('Larder wall cloth rail',(.13,2.47,1.61),(.13,3.04,1.61),.012,mats['steel'])\", \"rod('Larder shoulder height cloth rail',(.14,4.77,1.61),(.97,4.77,1.61),.012,mats['steel'])\\n for xx in (.14,.97): rod('Larder towel rail upright',(xx,4.77,.90),(xx,4.77,1.61),.009,mats['steel'])\\n towel((.57,4.77,1.63),mats,.35)\")\ns=s.replace(\"towel((7.22,1.565,.97),mats,.25)\",\"rod('Pass front towel rail',(7.0,1.52,.86),(7.45,1.52,.86),.012,mats['steel'])\\n for xx in (7.0,7.45): rod('Pass towel rail standoff',(xx,1.52,.86),(xx,1.595,.86),.009,mats['steel'])\\n towel((7.22,1.52,.88),mats,.25)\")\np.write_text(s)\np=Path('scripts/food.py');s=p.read_text().replace(\"(.078,.005),(.083,.005)\",\"(.078,0),(.083,0)\");p.write_text(s)\nPY\n/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/blender-4.5.13-linux-x64/blender -b --python-expr \"import sys; sys.path.insert(0,'scripts'); import bpy,occupancy; names='steel polished heatsteel darksteel rubber white cream black red green yellow blue translucent glass wood cloth paper ink brass lightwarm lightcool food_red food_green food_yellow food_brown'.split(); mats={n:bpy.data.materials.new(n) for n in names}; occupancy.build(mats); print('OCCUPANCY_BUILD_OK',len(bpy.data.objects))\""],"cwd":"file:///lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/kitchen","parsed_cmd":[{"type":"unknown","cmd":"python - <<'PY'\nfrom pathlib import Path\np=Path('scripts/occupancy.py')\ns=p.read_text().replace(\"rod('Larder wall cloth rail',(.13,2.47,1.61),(.13,3.04,1.61),.012,mats['steel'])\", \"rod('Larder shoulder height cloth rail',(.14,4.77,1.61),(.97,4.77,1.61),.012,mats['steel'])\\n for xx in (.14,.97): rod('Larder towel rail upright',(xx,4.77,.90),(xx,4.77,1.61),.009,mats['steel'])\\n towel((.57,4.77,1.63),mats,.35)\")\ns=s.replace(\"towel((7.22,1.565,.97),mats,.25)\",\"rod('Pass front towel rail',(7.0,1.52,.86),(7.45,1.52,.86),.012,mats['steel'])\\n for xx in (7.0,7.45): rod('Pass towel rail standoff',(xx,1.52,.86),(xx,1.595,.86),.009,mats['steel'])\\n towel((7.22,1.52,.88),mats,.25)\")\np.write_text(s)\np=Path('scripts/food.py');s=p.read_text().replace(\"(.078,.005),(.083,.005)\",\"(.078,0),(.083,0)\");p.write_text(s)\nPY\n/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/blender-4.5.13-linux-x64/blender -b --python-expr \"import sys; sys.path.insert(0,'scripts'); import bpy,occupancy; names='steel polished heatsteel darksteel rubber white cream black red green yellow blue translucent glass wood cloth paper ink brass lightwarm lightcool food_red food_green food_yellow food_brown'.split(); mats={n:bpy.data.materials.new(n) for n in names}; occupancy.build(mats); print('OCCUPANCY_BUILD_OK',len(bpy.data.objects))\""}],"source":"unified_exec_startup","status":"completed","stdout":"OCCUPANCY_BUILD_OK 494\nBlender 4.5.13 LTS (hash daeeeca98fb0 built 2026-08-25 01:31:19)\n\nBlender quit\n","stderr":"","aggregated_output":"OCCUPANCY_BUILD_OK 494\nBlender 4.5.13 LTS (hash daeeeca98fb0 built 2026-08-25 01:31:19)\n\nBlender quit\n","exit_code":0,"duration":{"secs":12,"nanos":719440487},"formatted_output":"OCCUPANCY_BUILD_OK 494\nBlender 4.5.13 LTS (hash daeeeca98fb0 built 2026-08-25 01:31:19)\n\nBlender quit\n"},"started_at_ms":1789012576965,"completed_at_ms":1789012589685}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:56:29.725Z","ordinal":70,"type":"event_msg","payload":{"type":"item_completed","thread_id":"01a08971-6519-7cf3-9399-e7f6b9686fbc","turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","item":{"type":"CommandExecution","id":"exec-97067288-69dd-44a9-bea6-27af6171bc5a","process_id":"6733","command":["/usr/bin/bash","-lc","python - <<'PY'\nfrom pathlib import Path\np=Path('scripts/occupancy.py')\ns=p.read_text().replace(\"rod('Larder wall cloth rail',(.13,2.47,1.61),(.13,3.04,1.61),.012,mats['steel'])\", \"rod('Larder shoulder height cloth rail',(.14,4.77,1.61),(.97,4.77,1.61),.012,mats['steel'])\\n for xx in (.14,.97): rod('Larder towel rail upright',(xx,4.77,.90),(xx,4.77,1.61),.009,mats['steel'])\\n towel((.57,4.77,1.63),mats,.35)\")\ns=s.replace(\"towel((7.22,1.565,.97),mats,.25)\",\"rod('Pass front towel rail',(7.0,1.52,.86),(7.45,1.52,.86),.012,mats['steel'])\\n for xx in (7.0,7.45): rod('Pass towel rail standoff',(xx,1.52,.86),(xx,1.595,.86),.009,mats['steel'])\\n towel((7.22,1.52,.88),mats,.25)\")\np.write_text(s)\np=Path('scripts/food.py');s=p.read_text().replace(\"(.078,.005),(.083,.005)\",\"(.078,0),(.083,0)\");p.write_text(s)\nPY\n/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/blender-4.5.13-linux-x64/blender -b --python-expr \"import sys; sys.path.insert(0,'scripts'); import bpy,occupancy; names='steel polished heatsteel darksteel rubber white cream black red green yellow blue translucent glass wood cloth paper ink brass lightwarm lightcool food_red food_green food_yellow food_brown'.split(); mats={n:bpy.data.materials.new(n) for n in names}; occupancy.build(mats); print('OCCUPANCY_BUILD_OK',len(bpy.data.objects))\""],"cwd":"file:///lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/bench/kitchen","parsed_cmd":[{"type":"unknown","cmd":"python - <<'PY'\nfrom pathlib import Path\np=Path('scripts/occupancy.py')\ns=p.read_text().replace(\"rod('Larder wall cloth rail',(.13,2.47,1.61),(.13,3.04,1.61),.012,mats['steel'])\", \"rod('Larder shoulder height cloth rail',(.14,4.77,1.61),(.97,4.77,1.61),.012,mats['steel'])\\n for xx in (.14,.97): rod('Larder towel rail upright',(xx,4.77,.90),(xx,4.77,1.61),.009,mats['steel'])\\n towel((.57,4.77,1.63),mats,.35)\")\ns=s.replace(\"towel((7.22,1.565,.97),mats,.25)\",\"rod('Pass front towel rail',(7.0,1.52,.86),(7.45,1.52,.86),.012,mats['steel'])\\n for xx in (7.0,7.45): rod('Pass towel rail standoff',(xx,1.52,.86),(xx,1.595,.86),.009,mats['steel'])\\n towel((7.22,1.52,.88),mats,.25)\")\np.write_text(s)\np=Path('scripts/food.py');s=p.read_text().replace(\"(.078,.005),(.083,.005)\",\"(.078,0),(.083,0)\");p.write_text(s)\nPY\n/lustre/fs11/portfolios/nvr/projects/nvr_elm_llm/users/haozhel/qihang/3dgen/blender-4.5.13-linux-x64/blender -b --python-expr \"import sys; sys.path.insert(0,'scripts'); import bpy,occupancy; names='steel polished heatsteel darksteel rubber white cream black red green yellow blue translucent glass wood cloth paper ink brass lightwarm lightcool food_red food_green food_yellow food_brown'.split(); mats={n:bpy.data.materials.new(n) for n in names}; occupancy.build(mats); print('OCCUPANCY_BUILD_OK',len(bpy.data.objects))\""}],"source":"unified_exec_startup","status":"completed","stdout":"OCCUPANCY_BUILD_OK 494\nBlender 4.5.13 LTS (hash daeeeca98fb0 built 2026-08-25 01:31:19)\n\nBlender quit\n","stderr":"","aggregated_output":"OCCUPANCY_BUILD_OK 494\nBlender 4.5.13 LTS (hash daeeeca98fb0 built 2026-08-25 01:31:19)\n\nBlender quit\n","exit_code":0,"duration":{"secs":12,"nanos":719440487},"formatted_output":"OCCUPANCY_BUILD_OK 494\nBlender 4.5.13 LTS (hash daeeeca98fb0 built 2026-08-25 01:31:19)\n\nBlender quit\n"},"started_at_ms":1789012576965,"completed_at_ms":1789012589685}}
{"timestamp":"2026-09-10T03:56:52.684Z","ordinal":79,"type":"response_item","payload":{"type":"custom_tool_call_output","id":"ctco_01a08976-164c-7d82-a045-b7b7d94cffb1","call_id":"call_1K6KmMOCd8q9FVXVgCd3jsAu","output":[{"type":"input_text","text":"Script completed\nWall time 0.6 seconds\nOutput:\n"},{"type":"input_text","text":"{\"chunk_id\":\"5e692e\",\"wall_time_seconds\":0.332244021,\"exit_code\":0,\"original_token_count\":0,\"output\":\"\"}"}],"internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012612.6843}}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:56:52.684Z","ordinal":79,"type":"response_item","payload":{"type":"custom_tool_call_output","id":"ctco_01a08976-164c-7d82-a045-b7b7d94cffb1","call_id":"call_1K6KmMOCd8q9FVXVgCd3jsAu","output":[{"type":"input_text","text":"Script completed\nWall time 0.6 seconds\nOutput:\n"},{"type":"input_text","text":"{\"chunk_id\":\"5e692e\",\"wall_time_seconds\":0.332244021,\"exit_code\":0,\"original_token_count\":0,\"output\":\"\"}"}],"internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012612.6843}}}
{"timestamp":"2026-09-10T03:57:08.614Z","ordinal":88,"type":"event_msg","payload":{"type":"item_completed","thread_id":"01a08971-6519-7cf3-9399-e7f6b9686fbc","turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","item":{"type":"AgentMessage","id":"msg_088f8f5d623dbe82016aa22a94951887d289c55331fec65098","content":[{"type":"Text","text":"Implemented `scripts/occupancy.py` and `scripts/food.py`: 491 added objects covering larder prep, open GN pans, knives, bread, squeeze bottles, plated meals, heat lamps, dockets, porcelain stacks, and supported draped towels.\n\nBlender construction passed with exit 0; both files compile. No renders or scene saves performed. Parent can integrate through `occupancy.build(mats)`."}],"phase":"final_answer"},"started_at_ms":1789012628614,"completed_at_ms":1789012628614}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:57:08.614Z","ordinal":88,"type":"event_msg","payload":{"type":"item_completed","thread_id":"01a08971-6519-7cf3-9399-e7f6b9686fbc","turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","item":{"type":"AgentMessage","id":"msg_088f8f5d623dbe82016aa22a94951887d289c55331fec65098","content":[{"type":"Text","text":"Implemented `scripts/occupancy.py` and `scripts/food.py`: 491 added objects covering larder prep, open GN pans, knives, bread, squeeze bottles, plated meals, heat lamps, dockets, porcelain stacks, and supported draped towels.\n\nBlender construction passed with exit 0; both files compile. No renders or scene saves performed. Parent can integrate through `occupancy.build(mats)`."}],"phase":"final_answer"},"started_at_ms":1789012628614,"completed_at_ms":1789012628614}}
{"timestamp":"2026-09-10T03:57:08.626Z","ordinal":89,"type":"response_item","payload":{"type":"message","id":"msg_088f8f5d623dbe82016aa22a94951887d289c55331fec65098","role":"assistant","content":[{"type":"output_text","text":"Implemented `scripts/occupancy.py` and `scripts/food.py`: 491 added objects covering larder prep, open GN pans, knives, bread, squeeze bottles, plated meals, heat lamps, dockets, porcelain stacks, and supported draped towels.\n\nBlender construction passed with exit 0; both files compile. No renders or scene saves performed. Parent can integrate through `occupancy.build(mats)`."}],"phase":"final_answer","internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012622.1816,"content_item_kinds":["unknown"]}}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:57:08.626Z","ordinal":89,"type":"response_item","payload":{"type":"message","id":"msg_088f8f5d623dbe82016aa22a94951887d289c55331fec65098","role":"assistant","content":[{"type":"output_text","text":"Implemented `scripts/occupancy.py` and `scripts/food.py`: 491 added objects covering larder prep, open GN pans, knives, bread, squeeze bottles, plated meals, heat lamps, dockets, porcelain stacks, and supported draped towels.\n\nBlender construction passed with exit 0; both files compile. No renders or scene saves performed. Parent can integrate through `occupancy.build(mats)`."}],"phase":"final_answer","internal_chat_message_metadata_passthrough":{"turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","create_time":1789012622.1816,"content_item_kinds":["unknown"]}}}
{"timestamp":"2026-09-10T03:57:08.905Z","ordinal":92,"type":"event_msg","payload":{"type":"task_complete","turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","last_agent_message":"Implemented `scripts/occupancy.py` and `scripts/food.py`: 491 added objects covering larder prep, open GN pans, knives, bread, squeeze bottles, plated meals, heat lamps, dockets, porcelain stacks, and supported draped towels.\n\nBlender construction passed with exit 0; both files compile. No renders or scene saves performed. Parent can integrate through `occupancy.build(mats)`.","started_at":1789012305,"completed_at":1789012628,"duration_ms":323584,"time_to_first_token_ms":9576}}
单行原文 · 未格式化
{"timestamp":"2026-09-10T03:57:08.905Z","ordinal":92,"type":"event_msg","payload":{"type":"task_complete","turn_id":"01a08971-658b-7a92-8d7c-510ecaed8a77","last_agent_message":"Implemented `scripts/occupancy.py` and `scripts/food.py`: 491 added objects covering larder prep, open GN pans, knives, bread, squeeze bottles, plated meals, heat lamps, dockets, porcelain stacks, and supported draped towels.\n\nBlender construction passed with exit 0; both files compile. No renders or scene saves performed. Parent can integrate through `occupancy.build(mats)`.","started_at":1789012305,"completed_at":1789012628,"duration_ms":323584,"time_to_first_token_ms":9576}}