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Found 2,475 Skills
LangChain LLM application framework with chains, agents, RAG, and memory for building AI-powered applications
Complete AI agent operating system setup with Kanban task management. Use when setting up multi-agent coordination, task tracking, or configuring an agent team. Includes theme selection (DBZ, One Piece, Marvel, etc.), workflow enforcement (all tasks through board), browser setup, GitHub integration, and memory enhancement (Supermemory, QMD).
Access paid services (verification, search, AI models, images, audio, browser automation) for AI agents via Sapiom. Use when building agents that need to verify phone/email, search the web, call AI models, generate images, convert text-to-speech, or automate browsers — without setting up vendor accounts.
Add email capabilities to AI agents using popular frameworks. Provides pre-built tools for TypeScript and Python frameworks including Vercel AI SDK, LangChain, Clawdbot, OpenAI Agents SDK, and LiveKit Agents. Use when integrating AgentMail with agent frameworks that need email send/receive tools.
Transform extracted engineer expertise into an actionable skill with progressive disclosure, allowing agents to find and apply relevant patterns for specific tasks.
Automatically sync Agents.md, claude.md and gemini.md files in the project to maintain content consistency. Supports automatic monitoring and manual triggering.
Conduct enterprise-grade research with multi-source synthesis, citation tracking, and verification. Use when user needs comprehensive analysis requiring 10+ sources, verified claims, or comparison of approaches. Triggers include "deep research", "comprehensive analysis", "research report", "compare X vs Y", or "analyze trends". Do NOT use for simple lookups, debugging, or questions answerable with 1-2 searches.
General Architecture Governance Specification, providing layering constraints, impact analysis, interface contracts, and dependency injection baselines. Suitable for architecture review, refactoring, and new module design of any multi-layer system.
Create non-technical documentation for project features in the docs/ folder. Use when documenting completed features, writing feature documentation, explaining how features work, or when the user asks to document the project or create docs for non-developers.
Patterns and architectures for building AI agents and workflows with LLMs. Use when designing systems that involve tool use, multi-step reasoning, autonomous decision-making, or orchestration of LLM-driven tasks.
Coordinate AI agent teams via a Kanban task board with local JSON storage. Enables multi-agent workflows with a Team Lead assigning work and Worker Agents executing tasks via heartbeat polling. Perfect for building AI agent command centers.
Build single-agent and multi-agent systems using Google's Agent Development Kit (ADK) in Python, Java, Go, or TypeScript. Use when creating AI agents with ADK, designing multi-agent architectures, implementing agent tools, configuring agent callbacks, managing agent state, orchestrating sequential/parallel/loop agent workflows, or when the user mentions ADK, google-adk, google agent development kit, agentic AI with Gemini, or agent orchestration with Google tools. Also use when setting up ADK projects, writing agent tests, deploying agents, or integrating MCP tools with ADK.