Agent skill
custom-ai-agents
Install this agent skill to your Project
npx add-skill https://github.com/Gaku52/claude-code-skills/tree/main/07-ai/custom-ai-agents
SKILL.md
日本語版
Custom AI Agents
AI agents grant LLMs the ability to act autonomously. This skill covers everything about AI agent development — from agent architecture, tool integration, and multi-agent systems to the MCP protocol and production deployment.
Target Audience
- Engineers designing and implementing AI agents
- Those looking to build more advanced LLM applications
- Those interested in multi-agent systems
Prerequisites
- Experience using LLM APIs
- Hands-on experience with TypeScript or Python
- Web development fundamentals
Learning Guide
00-fundamentals — Agent Fundamentals
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01-architecture — Architecture
| # | File | Description |
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02-tools — Tools and Frameworks
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03-advanced — Advanced Topics
| # | File | Description |
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04-deployment — Deployment and Operations
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Quick Reference
Agent Pattern Selection:
Simple task → Single Agent + Tool Use
Complex task → Plan-and-Execute
Mixed specialties → Multi-Agent
Human approval needed → Human-in-the-Loop
Many external tools → MCP Integration
Framework Selection:
Lightweight, flexible → Anthropic SDK directly
Full-stack → LangChain / LangGraph
Multi-agent → CrewAI / AutoGen
TypeScript → Vercel AI SDK
References
- Anthropic. "Tool Use Documentation." docs.anthropic.com, 2024.
- LangChain. "Documentation." langchain.com/docs, 2024.
- Anthropic. "MCP Specification." modelcontextprotocol.io, 2024.
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