generate-subsystem-skills — aiproject generate-subsystem-skills, llamafarm, community, aiproject, ide skills, chatgpt, edge-computing, finetuning-llms, llama3, llama4

v1.0.0

이 스킬 정보

Claude Code와 같은 보안, 성능 및 언어 특정 최선의 실践에 대한 전문적인 기술이 필요한 AI 코딩 어시스턴트에 적합합니다. Deploy any AI model, agent, database, RAG, and pipeline locally or remotely in minutes

# Core Topics

llama-farm llama-farm
[825]
[49]
Updated: 3/17/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 9/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review
Review Score
9/11
Quality Score
67
Canonical Locale
en
Detected Body Locale
en

Claude Code와 같은 보안, 성능 및 언어 특정 최선의 실践에 대한 전문적인 기술이 필요한 AI 코딩 어시스턴트에 적합합니다. Deploy any AI model, agent, database, RAG, and pipeline locally or remotely in minutes

이 스킬을 사용하는 이유

Python, Go, TypeScript 및 React와 같은 언어와 FastAPI, Celery 및 Pydantic와 같은 프레임워크를 활용하여 서브시스템 특정 기술을 생성하고 Grep 및 Read와 같은 도구를 사용하여 코드 패턴 분석을 통해 에이전트를 강화합니다.

최적의 용도

Claude Code와 같은 보안, 성능 및 언어 특정 최선의 실践에 대한 전문적인 기술이 필요한 AI 코딩 어시스턴트에 적합합니다.

실행 가능한 사용 사례 for generate-subsystem-skills

여러 하위 시스템에 대한 공유 언어 기술 생성
보안 및 성능 최적화를 위한 하위 시스템 특정 기술 생성
Grep 및 Read를 사용한 코드 패턴 분석을 통한 이상적인 접근 방법 문서화

! 보안 및 제한 사항

  • 하위 시스템 정의 및 종속 파일에 대한 액세스가 필요합니다.
  • 하위 시스템 레지스트리에 지정된 언어 및 프레임워크로 제한됩니다.
  • 효율적인 하위 에이전트 실행을 위해 병렬 처리 기능이 필요합니다.

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

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Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is generate-subsystem-skills?

Claude Code와 같은 보안, 성능 및 언어 특정 최선의 실践에 대한 전문적인 기술이 필요한 AI 코딩 어시스턴트에 적합합니다. Deploy any AI model, agent, database, RAG, and pipeline locally or remotely in minutes

How do I install generate-subsystem-skills?

Run the command: npx killer-skills add llama-farm/llamafarm. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for generate-subsystem-skills?

Key use cases include: 여러 하위 시스템에 대한 공유 언어 기술 생성, 보안 및 성능 최적화를 위한 하위 시스템 특정 기술 생성, Grep 및 Read를 사용한 코드 패턴 분석을 통한 이상적인 접근 방법 문서화.

Which IDEs are compatible with generate-subsystem-skills?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for generate-subsystem-skills?

하위 시스템 정의 및 종속 파일에 대한 액세스가 필요합니다.. 하위 시스템 레지스트리에 지정된 언어 및 프레임워크로 제한됩니다.. 효율적인 하위 에이전트 실행을 위해 병렬 처리 기능이 필요합니다..

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add llama-farm/llamafarm. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use generate-subsystem-skills immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

generate-subsystem-skills

Install generate-subsystem-skills, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

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

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