generate-subsystem-skills
Generates specialized coding skills for monorepo subsystems.
Install
mkdir -p .claude/skills/generate-subsystem-skills && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/2786" && unzip -o skill.zip -d .claude/skills/generate-subsystem-skills && rm skill.zipInstalls to .claude/skills/generate-subsystem-skills
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Generate specialized skills for each subsystem in the monorepo. Creates shared language skills and subsystem-specific checklists for high-quality AI code generation.Key capabilities
- →Generate shared language-specific skills
- →Generate subsystem-specific skills
- →Analyze monorepo subsystem definitions
- →Identify ideal coding patterns
- →Create framework-specific checklist files
How it works
The skill analyzes subsystem definitions and dependency files within a monorepo, then launches sub-agents to generate shared language skills and subsystem-specific skills with ideal patterns and checklists.
Inputs & outputs
When to use generate-subsystem-skills
- →Create subsystem-specific coding skills
- →Standardize monorepo best practices
- →Generate specialized linting or checklists
About this skill
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, commongo-skills/- Used by: clitypescript-skills/- Used by: designer, electronreact-skills/- Used by: designer
Subsystem-Specific Skills (8)
cli-skills/- Cobra, Bubbletea patternsserver-skills/- FastAPI, Celery, Pydantic patternsrag-skills/- LlamaIndex, ChromaDB patternsruntime-skills/- PyTorch, Transformers patternsdesigner-skills/- TanStack Query, Tailwind, Radix patternselectron-skills/- Electron IPC, security patternsconfig-skills/- Pydantic, JSONSchema patternscommon-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:
-
Python Skills Agent - Analyze Python subsystems (server, rag, runtime, config, common), identify ideal patterns, generate
python-skills/ -
Go Skills Agent - Analyze CLI subsystem, identify ideal Go patterns, generate
go-skills/ -
TypeScript Skills Agent - Analyze designer and electron, identify ideal TS patterns, generate
typescript-skills/ -
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:
- Read the subsystem's dependency files (package.json, pyproject.toml, go.mod)
- Analyze code patterns using Grep and Read
- Generate SKILL.md that links to shared language skills
- Generate framework-specific checklist files
- 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
How it compares
This skill automates the creation of tailored AI coding skills for each part of a monorepo, ensuring adherence to specific best practices and language standards across diverse components.
Compared to similar skills
generate-subsystem-skills side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| generate-subsystem-skills (this skill) | 1 | 7mo | No flags | Advanced |
| generating-api-sdks | 1 | 27d | Review | Advanced |
| common-performance-engineering | 0 | 1mo | No flags | Intermediate |
| mcp-builder | 136 | 3mo | Review | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
More by llama-farm
View all by llama-farm →You might also like
generating-api-sdks
jeremylongshore
Generate client SDKs in multiple languages from OpenAPI specifications. Use when generating client libraries for API consumption. Trigger with phrases like "generate SDK", "create client library", or "build API SDK".
common-performance-engineering
HoangNguyen0403
Enforce universal standards for high-performance development. Use when profiling bottlenecks, reducing latency, fixing memory leaks, improving throughput, or optimizing algorithm complexity in any language.
mcp-builder
anthropics
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).
architecture-patterns
wshobson
Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use when architecting complex backend systems or refactoring existing applications for better maintainability.
deepwiki-rs
sopaco
AI-powered Rust documentation generation engine for comprehensive codebase analysis, C4 architecture diagrams, and automated technical documentation. Use when Claude needs to analyze source code, understand software architecture, generate technical specs, or create professional documentation from any programming language.
copilot-sdk
github
Build agentic applications with GitHub Copilot SDK. Use when embedding AI agents in apps, creating custom tools, implementing streaming responses, managing sessions, connecting to MCP servers, or creating custom agents. Triggers on Copilot SDK, GitHub SDK, agentic app, embed Copilot, programmable agent, MCP server, custom agent.