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Generate valid AGENTS.md files for repositories according to AAIF standards. Use when Claude needs to create or update AGENTS.md files that document AI agents in a repository following standard format and best practices.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | agents-md-gen |
| description | Generate valid AGENTS.md files for repositories according to AAIF standards. Use when Claude needs to create or update AGENTS.md files that document AI agents in a repository following standard format and best practices. |
This skill generates AGENTS.md files that document AI agents in a repository according to AAIF (AI Agent Interoperability Framework) standards. It analyzes a repository's structure, identifies agent configurations and conventions, and outputs a properly formatted AGENTS.md that makes the repo AI-tool-friendly.
Use this skill any time you set up a new agent-enabled project or onboard an existing repo to the AAIF standard.
# From the repo root, invoke the skill
/agents-md-gen
# The skill will scan your repo and write AGENTS.md
The output file is placed at the repository root as AGENTS.md.
.claude/, skills/, agents/, config YAMLs)The generation logic is implemented in the supporting script to maintain consistency and follow AAIF standards.
mcp-builder — Build the MCP servers that AGENTS.md documentsimplementation-specialist — Implement the agent workflows referenced in AGENTS.mdaudit-logging-system — Add audit logging to the agents documented hereOptimize Three.js and WebGL performance, reduce GPU load, suggest fallback UI strategies, and maintain 60fps experience.
Agent-to-Agent (A2A) messaging system for direct communication between Cloud and Local agents. Replaces file-based handoffs with real-time messaging while maintaining vault as audit record. Supports task delegation, status updates, approval requests, and result delivery between distributed AI Employee instances. Use when coordinating multiple Claude Code agents across cloud and local environments.
Implements the core Customer Success Agent using OpenAI Agents SDK. Manages the orchestration of tool calls (search, ticket creation, etc.), conversation logic, and state management. Use when Claude needs to create or modify Customer Success Agent implementations with OpenAI Agents SDK, orchestrate multiple tools, manage conversation flows, or handle persistent state across interactions.
Design learning experiences for AI-native software development, integrating the Three Roles Framework (AI as Teacher/Student/Co-Worker), co-learning partnership pedagogy, and "Specs Are the New Syntax" paradigm into programming curriculum. Use this skill when educators need to prepare students for professional AI-driven development workflows, teach effective specification-first collaboration, or balance AI assistance with foundational learning goals. This skill helps create lessons that leverage AI tools appropriately while ensuring students build independent capability, bidirectional learning patterns, and ethical AI use practices. Aligned with Constitution v4.0.1.
Expert in LLM integration (Claude/GPT), RAG systems for self-learning, and WhatsApp Business API for remote approval workflows. Use when: (1) Designing prompts for Claude or GPT models with system prompts and few-shot learning, (2) Implementing multi-agent orchestration with specialized agent prompts, (3) Setting up RAG systems with vector databases (Pinecone, ChromaDB, Weaviate), (4) Implementing document chunking, embedding generation, and retrieval strategies, (5) Building WhatsApp approval workflows with interactive messages and buttons, (6) Integrating feedback loops for continuous learning, (7) Optimizing LLM API calls with error handling and retries, (8) Creating message templates for WhatsApp Business API. Provides prompt templates, RAG implementation patterns, WhatsApp message templates, and comprehensive reference documentation.
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