菜单
Use when generating boilerplate code, __init__.py files, or test scaffolds. Provides scripts that generate consistent, convention-following code.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Create a subsystem orientation skill after deep research on a stable, non-churning part of the codebase when no skill exists for it. Use when you have just read many files, traced call chains, or explored architecture to understand how a subsystem works — and that knowledge should be captured to prevent the same context burn on every future session touching that area. Triggers include: had to explore 5+ files to understand one concept, traced IPC/process/worker/pipeline topology manually, or answered "how does X actually work" from scratch.
Use when executing implementation plans produced by the feature-planning skill. Orchestrates execution subagents (one plan phase at a time), dispatches review subagents for thorough quality enforcement after each plan, and manages fix cycles when review finds issues. Trigger when: (1) the user explicitly says "execute the plans", "implement the feature", or "work through the plans"; OR (2) the user asks to start implementation and every plan for the single feature being executed (all lettered plans A–Z for that specific feature slug, covering its full scope) exists and is schema-valid in artifacts/plans/pending/TASK-*-{A..Z}-*.md. Not for single-plan execution — use plan_complete_step directly for those.
Use when decomposing a major feature design into dependency-ordered implementation plans. Handles the full pipeline from design document to validated, cross-referenced plan files with minimal drift. Trigger when **any** of the following are true, with user requests (4) taking priority over the other conditions: (1) the feature involves 3+ implementation parts, (2) it spans multiple architectural layers, (3) it requires coordination across multiple sessions, or (4) the user explicitly asks to break down a design doc into implementation plans. Not for single plans or simple tasks — use the Plan subagent directly for those.
Use when creating or updating VS Code Copilot agent hook files in .github/hooks. Covers all 8 hook event types (PreToolUse, PostToolUse, SessionStart, SubagentStart, SubagentStop, Stop, UserPromptSubmit, PreCompact), the stdin/stdout JSON contract, permissionDecision allow/deny/ask, exit code semantics, hook command properties, and repository conventions for Python validator scripts.
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
| name | code-generation |
| description | Use when generating boilerplate code, __init__.py files, or test scaffolds. Provides scripts that generate consistent, convention-following code. |
When to use: When creating new modules, updating exports, or scaffolding tests.
Purpose: Auto-generate __init__.py files with proper __all__ exports.
Use when:
Usage:
python scripts/generate_inits.py
How it works:
__init__.py with __all__ listing public exportsscripts/configs/generate_inits_config.ymlWhat it exports:
_*)Decision rule: After adding public functions to a module, run this to update exports.
Purpose: Generate test scaffolds with smart assertions and proper fixtures.
Use when:
Usage:
# Generate tests for a module
python scripts/generate_tests.py nomarr.services.domain.tagging_svc --output tests/unit/services/test_tagging_svc.py
# Preview without writing
python scripts/generate_tests.py nomarr.components.ml.ml_embed_comp --preview
# Specify layer for auto-fixture selection
python scripts/generate_tests.py nomarr.workflows.processing.process_file_wf --layer workflows
Generated tests include:
Create the module with your functions/classes
Update exports:
python scripts/generate_inits.py
Generate test scaffold:
python scripts/generate_tests.py nomarr.components.new_comp --output tests/unit/components/test_new_comp.py --preview
# If preview looks good:
python scripts/generate_tests.py nomarr.components.new_comp --output tests/unit/components/test_new_comp.py
Fill in test implementations
# After adding/removing public functions:
python scripts/generate_inits.py
# Review changes:
git diff nomarr/*/__init__.py
Located at scripts/configs/generate_inits_config.yml:
# Packages to scan
packages:
- nomarr.services
- nomarr.workflows
- nomarr.components
- nomarr.persistence
- nomarr.helpers
# Names to never export
banned_exports:
- TYPE_CHECKING
- annotations
generate_inits.py after adding public symbols — keeps exports consistent--preview before writing test files — verify structure is correct