본문으로 건너뛰기
cccskills
무료GitHub에 공개

generate-subsystem-skills

Generate specialized skills for each subsystem in the monorepo. Creates shared language skills and subsystem-specific checklists for high-quality AI code generation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(2)

  • SKILL.md4.6 KB
  • subsystem-registry.md4.8 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Generate Subsystem Skills

This skill analyzes each subsystem in the LlamaFarm monorepo and generates specialized Claude Code skills for security, performance, and language-specific best practices.

Usage

/generate-subsystem-skills

What Gets Generated

Shared Language Skills (4)

  • python-skills/ - Used by: server, rag, runtime, config, common
  • go-skills/ - Used by: cli
  • typescript-skills/ - Used by: designer, electron
  • react-skills/ - Used by: designer

Subsystem-Specific Skills (8)

  • cli-skills/ - Cobra, Bubbletea patterns
  • server-skills/ - FastAPI, Celery, Pydantic patterns
  • rag-skills/ - LlamaIndex, ChromaDB patterns
  • runtime-skills/ - PyTorch, Transformers patterns
  • designer-skills/ - TanStack Query, Tailwind, Radix patterns
  • electron-skills/ - Electron IPC, security patterns
  • config-skills/ - Pydantic, JSONSchema patterns
  • common-skills/ - HuggingFace Hub patterns

Generation Process

Step 1: Read Registry

Load subsystem definitions from subsystem-registry.md.

Step 2: Generate Shared Language Skills

Launch sub-agents IN PARALLEL to generate:

  1. Python Skills Agent - Analyze Python subsystems (server, rag, runtime, config, common), identify ideal patterns, generate python-skills/

  2. Go Skills Agent - Analyze CLI subsystem, identify ideal Go patterns, generate go-skills/

  3. TypeScript Skills Agent - Analyze designer and electron, identify ideal TS patterns, generate typescript-skills/

  4. React Skills Agent - Analyze designer, identify ideal React 18 patterns, generate react-skills/

Step 3: Generate Subsystem Skills

Launch sub-agents IN PARALLEL for each subsystem:

For each subsystem, the agent should:

  1. Read the subsystem's dependency files (package.json, pyproject.toml, go.mod)
  2. Analyze code patterns using Grep and Read
  3. Generate SKILL.md that links to shared language skills
  4. Generate framework-specific checklist files
  5. Write all files to .claude/skills/{subsystem}-skills/

Step 4: Report Summary

After all agents complete, report:

  • Number of skills generated
  • Total files created
  • Any errors encountered

Sub-Agent Prompt Templates

For Shared Language Skills

You are generating a shared {LANGUAGE} skills directory for Claude Code.

Analyze these subsystems that use {LANGUAGE}:
{SUBSYSTEM_PATHS}

Your task:
1. Read key files to understand patterns used
2. When patterns vary, document the IDEAL approach (not inconsistencies)
3. Reference industry best practices
4. Generate files in .claude/skills/{LANGUAGE}-skills/

Files to generate:
- SKILL.md (overview, ~100 lines)
- patterns.md (idiomatic patterns)
- error-handling.md
- testing.md
- security.md
- {additional language-specific files}

Each checklist item should have:
- Description of what to check
- Search pattern (grep command)
- Pass/fail criteria
- Severity level

For Subsystem Skills

You are generating subsystem-specific skills for {SUBSYSTEM} in Claude Code.

Directory: {PATH}
Tech Stack: {TECH_STACK}
Links to: {SHARED_SKILLS}

Your task:
1. Read dependency files and key source files
2. Identify framework-specific patterns
3. Generate SKILL.md that links to shared language skills
4. Generate framework-specific checklists

Files to generate:
- SKILL.md (overview with links to shared skills)
- {framework}.md for each framework used
- performance.md (subsystem-specific optimizations)

Remember: Document IDEAL patterns, not existing inconsistencies.

Key Principle

Prescribe ideal patterns - When the codebase has inconsistent patterns, the generated skills should document the BEST practice according to industry standards, not codify existing inconsistencies.


Output Location

All skills are written to .claude/skills/ with this structure:

.claude/skills/
├── python-skills/      # Shared
├── go-skills/          # Shared
├── typescript-skills/  # Shared
├── react-skills/       # Shared
├── cli-skills/         # Subsystem
├── server-skills/      # Subsystem
├── rag-skills/         # Subsystem
├── runtime-skills/     # Subsystem
├── designer-skills/    # Subsystem
├── electron-skills/    # Subsystem
├── config-skills/      # Subsystem
└── common-skills/      # Subsystem

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

CLI best practices for LlamaFarm. Covers Cobra, Bubbletea, Lipgloss patterns for Go CLI development.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

llama-farm/llamafarm8362026년 6월 10일 업데이트

Comprehensive code review for diffs. Analyzes changed code for security vulnerabilities, anti-patterns, and quality issues. Auto-detects domain (frontend/backend) from file paths.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

llama-farm/llamafarm8362026년 6월 10일 업데이트

Commit changes, push to GitHub, and open a PR. Includes quality checks (security, patterns, simplification). Use --quick to skip checks.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

llama-farm/llamafarm8362026년 6월 10일 업데이트

Best practices for the Common utilities package in LlamaFarm. Covers HuggingFace Hub integration, GGUF model management, and shared utilities.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

llama-farm/llamafarm8362026년 6월 10일 업데이트

Configuration module patterns for LlamaFarm. Covers Pydantic v2 models, JSONSchema generation, YAML processing, and validation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

llama-farm/llamafarm8362026년 6월 10일 업데이트

Designer subsystem patterns for LlamaFarm. Covers React 18, TanStack Query, TailwindCSS, and Radix UI.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

llama-farm/llamafarm8362026년 6월 10일 업데이트

llama-farm의 스킬 모두 보기

이 스킬의 문제 신고