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Found 4,984 Skills
Guides the agent through building LLM-powered applications with LangChain and stateful agent workflows with LangGraph. Triggered when the user asks to "create an AI agent", "build a LangChain chain", "create a LangGraph workflow", "implement tool calling", "build RAG pipeline", "create a multi-agent system", "define agent state", "add human-in-the-loop", "implement streaming", or mentions LangChain, LangGraph, chains, agents, tools, retrieval augmented generation, state graphs, or LLM orchestration.
Orchestrate parallel scientist agents for comprehensive research with AUTO mode
Show agent flow trace timeline and summary
Develop agentic software and multi-agent systems using Google ADK in Python
Create install.md files optimized for AI agent execution. Use for ANY question about install.md files or request to create/review installation documentation for autonomous agent use.
Run Microsoft's eval-recipes benchmarks to validate amplihack improvements against baseline agents. Auto-activates when testing improvements, running evals, or benchmarking changes.
Implement ReasoningBank adaptive learning with AgentDBs 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.
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).
Headless browser automation using Vercel's agent-browser CLI. 93% less context than Playwright MCP. Snapshot + refs workflow with element references. Use when automating browser tasks, web scraping, form filling, or content capture.
Generate structured agent prompts with FOCUS/EXCLUDE templates for task delegation. Use when breaking down complex tasks, launching parallel specialists, coordinating multiple agents, creating agent instructions, determining execution strategy, or preventing file path collisions. Handles task decomposition, parallel vs sequential logic, scope validation, and retry strategies.
AI agents: autonomous agents, multi-agent systems, LangChain, LlamaIndex, MCP.
Expert prompt optimization for LLMs and AI systems. Use PROACTIVELY when building AI features, improving agent performance, or crafting system prompts. Masters prompt patterns and techniques.