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Found 2,167 Skills
Meta-skill: helps create an AGENTS.md for a new project by guiding the user through selecting the right profile from the agentic library and running the compose command. Also helps create a custom AGENTS.md from scratch when no profile fits. Invoked when the user asks to set up agent instructions, create AGENTS.md, or configure agents for a project.
Initialize, validate, and troubleshoot Deep Agents projects in Python or JavaScript using the `deepagents` package. Use when users need to create agents with built-in planning/filesystem/subagents, configure middleware/backends/checkpointing/HITL, migrate from `create_react_agent` or `create_agent`, scaffold projects with repo scripts, validate agent config files, and confirm compatibility with current LangChain/LangGraph/LangSmith docs.
Audit and prune bloated CLAUDE.md or AGENTS.md context files using evidence-based criteria from research on what actually helps coding agents. Use when a user asks to trim, audit, review, or improve their CLAUDE.md, AGENTS.md, or any repository context file for AI coding agents.
Meta-skill for making the agent self-improving. Covers updating AGENTS.md, creating new skills from repeated workflows, and deciding what to systematize. Invoke after completing tasks, when noticing repeated friction, or at session end.
Create or update CLAUDE.md and AGENTS.md files following official best practices. Use when asked to create, update, audit, or improve project configuration files for AI agents, or when users mention "CLAUDE.md", "AGENTS.md", "agent config", or "agent instructions".
Use when completing development phases or branches to identify and update CLAUDE.md or AGENTS.md files that may have become stale - analyzes what changed, determines affected contracts and documentation, and coordinates updates
Integrate OpenAI Agents SDK with You.com MCP server - Hosted and Streamable HTTP support for Python and TypeScript. - MANDATORY TRIGGERS: OpenAI Agents SDK, OpenAI agents, openai-agents, @openai/agents, integrating OpenAI with MCP - Use when: developer mentions OpenAI Agents SDK, needs MCP integration with OpenAI agents
Manage Cursor Cloud Agents via the API. Launch agents, list running agents, check status, get conversation history, send follow-ups, stop or delete agents, and pull agent branch changes into the local repo. Use when the user mentions cloud agents, background agents, launching a task on a repo, checking agent status, or pulling agent changes.
Analyze repository structure and generate or update standardized AGENTS.md files that serve as contributor guides for AI agents. Supports both single-repo and monorepo structures. Measures LOC to determine character limits and produces structured documents covering overview, folder structure, patterns, conventions, and working agreements. Update mode refreshes only the standard sections while preserving user-defined custom sections. Use when setting up a new repository, onboarding AI agents to an existing codebase, updating an existing AGENTS.md, or when the user mentions AGENTS.md.
Authors and structures professional-grade agent skills following the agentskills.io spec. Use when creating new skill directories, drafting procedural instructions, or optimizing metadata for discoverability. Don't use for general documentation, non-agentic library code, or README files.
Guide for creating, refactoring, and optimizing AGENTS.md files (and CLAUDE.md files) for AI coding agent repositories. Use when the user wants to create a new AGENTS.md, refactor an existing one, audit their AGENTS.md for bloat or staleness, apply progressive disclosure principles, set up AGENTS.md in a monorepo, or improve how their AI coding agents behave via repository configuration files. Also applies to CLAUDE.md files (Claude Code's equivalent).
Amazon Bedrock Agents for building autonomous AI agents with foundation model orchestration, action groups, knowledge bases, and session management. Use when creating AI agents, orchestrating multi-step workflows, integrating tools with LLMs, building conversational agents, implementing RAG patterns, managing agent sessions, deploying production agents, or connecting knowledge bases to agents.