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Found 2,167 Skills
OpenAI Agents SDK (Python) development. Use when building AI agents, multi-agent workflows, tool integrations, or streaming applications with the openai-agents package.
Deep Agents framework — architectural decisions (when to use Deep Agents vs alternatives, backend strategies, subagent design, middleware approaches) AND code review (bugs, anti-patterns, improvements when reviewing Deep Agents code). Use when working with Deep Agents — designing a new system or reviewing existing code.
Builds AI agents on Cloudflare using the Agents SDK with state management, real-time WebSockets, scheduled tasks, tool integration, and chat capabilities. Generates production-ready agent code deployed to Workers. Use when: user wants to "build an agent", "AI agent", "chat agent", "stateful agent", mentions "Agents SDK", needs "real-time AI", "WebSocket AI", or asks about agent "state management", "scheduled tasks", or "tool calling".
Deep codebase initialization with hierarchical AGENTS.md documentation
Build AI agents with Strands Agents SDK. Use when developing model-agnostic agents, implementing ReAct patterns, creating multi-agent systems, or building production agents on AWS. Triggers on Strands, Strands SDK, model-agnostic agent, ReAct agent.
AGENTS.md 거버넌스 시스템을 분석·생성하는 마스터 프롬프트. 현재 프로젝트를 분석하여 루트 AGENTS.md와 하위 AGENTS.md를 즉시 생성하고, CLAUDE.md에 @AGENTS.md 링크를 추가한다. "AGENTS.md 만들어줘", "에이전트 규칙 만들어줘", "/agents-md" 호출 시 반드시 실행하라.
Update AGENTS.md and agent_docs/ following best practices. Use when modifying agent guidelines, adding new documentation, or restructuring agent instructions.
Interactive workflow to generate a full-lifecycle AGENTS.md using semantic AST/LSP analysis and chained user interviews.
Set up hierarchical Intent Layer (AGENTS.md files) for codebases. Use when initializing a new project, adding context infrastructure to an existing repo, user asks to set up AGENTS.md, add intent layer, make agents understand the codebase, or scaffolding AI-friendly project documentation.
Use when "LangChain", "LLM chains", "ReAct agents", "tool calling", or asking about "RAG pipelines", "conversation memory", "document QA", "agent tools", "LangSmith"
Onboarding entrypoint for agents-cli in Agent Platform. It should be used when the user wants to "create a new agent", "develop an agent", "build an agent using ADK", "run the agent locally", "debug agent code", "test an agent", "evaluate an agent", "deploy an agent", "publish an agent", "monitor an agent", or needs the ADK (Agent Development Kit) development lifecycle.
Use when working with AWS Strands Agents SDK or Amazon Bedrock AgentCore platform for building AI agents. Provides architecture guidance, implementation patterns, deployment strategies, observability, quality evaluations, multi-agent orchestration, and MCP server integration.