found 107 skills in registry
Builds Agent-to-Agent (A2A) servers and clients following Google's open protocol for agent interoperability. Use when the user wants to create an A2A-compliant agent, build an Agent Card, implement task management, connect agents across frameworks, set up agent discovery, handle streaming responses, implement push notifications, or orchestrate multi-agent workflows. Trigger words: a2a, agent to agent, agent2agent, a2a protocol, a2a server, a2a client, agent card, agent interoperability, agent co
Run AI agent code safely in isolated sandboxes with resource limits, audit trails, and kill switches. Use when someone asks to "sandbox my agent", "run agent code safely", "add guardrails to AI agent", "isolate agent execution", "audit agent actions", "prevent agent from deleting files", "restrict agent permissions", or "add safety controls to AI coding agent". Covers Docker isolation, filesystem restrictions, network policies, resource locking, and comprehensive audit logging.
You are an expert in AG2 (formerly AutoGen), the open-source multi-agent conversation framework. You help developers build systems where multiple AI agents collaborate through structured conversations — with tool use, human-in-the-loop, code execution, group chat orchestration, and nested conversations — for complex tasks like software development, research, and data analysis.
Build software with Claude Code, the AI-powered CLI coding agent. Use when a user asks to set up Claude Code, configure CLAUDE.md project files, use slash commands, manage permissions, create hooks, or optimize agentic coding workflows.
You are an expert in Mastra, the TypeScript framework for building AI agents, RAG pipelines, and workflows. You help developers create production AI applications with type-safe agent definitions, tool integration, vector-based knowledge retrieval, multi-step workflows with branching and error handling, and integration with 50+ third-party services — designed for TypeScript teams who want agent capabilities without Python dependencies.
Set up, configure, and manage PicoClaw — an ultra-lightweight personal AI assistant built in Go. Use when the user mentions "picoclaw," "pico claw," "lightweight AI assistant," or wants to deploy a personal AI agent on low-resource hardware (Raspberry Pi, RISC-V boards). Covers installation, LLM provider configuration, messaging gateway setup (Telegram, Discord, Slack, LINE, DingTalk), scheduled tasks, heartbeat, workspace layout, security sandbox, and Docker deployment.
Coordinate multiple AI agents working together on complex tasks — routing, handoffs, consensus, memory sharing, and quality gates. Use when tasks involve building multi-agent systems, coordinating specialist agents in a pipeline, implementing agent-to-agent communication, designing swarm architectures, setting up agent orchestration frameworks, or building autonomous agent teams with supervision and quality control. Covers hierarchical, mesh, and pipeline topologies.
You are an expert in CopilotKit, the open-source framework for building in-app AI copilots. You help developers add AI-powered features to React applications — chat sidebars, AI-assisted text editing, contextual suggestions, and autonomous agents that can read app state, call actions, and modify the UI — turning any React app into an AI-native experience.
You are an expert in Browser Use, the Python library that lets AI agents control a web browser. You help developers build agents that can navigate websites, fill forms, click buttons, extract data, and complete multi-step web tasks — using vision and DOM understanding to interact with any website like a human would.
You are an expert in the OpenAI Agents SDK (formerly Swarm), the official framework for building multi-agent systems. You help developers create agents with tool calling, guardrails, agent handoffs, streaming, tracing, and MCP integration — building production-grade AI agents that coordinate, delegate tasks, and execute tools with built-in safety controls.
You are an expert in Composio, the platform that gives AI agents access to 250+ external tools and APIs with managed authentication. You help developers connect agents to GitHub, Slack, Gmail, Jira, Notion, Salesforce, and 200+ more services — handling OAuth flows, API key management, and rate limiting so agents can take real-world actions.
You are an expert in PydanticAI, the Python agent framework built by the Pydantic team. You help developers create type-safe AI agents with structured outputs, dependency injection, tool definitions, streaming, and model-agnostic design — leveraging Pydantic for validation and type safety throughout the agent lifecycle.
Run autonomous AI-driven penetration tests on web applications using tools like Shannon, PentAGI, and similar frameworks. Use when tasks involve setting up automated penetration testing pipelines, combining AI agents with security tools (nmap, subfinder, nuclei, sqlmap), building autonomous exploit chains, generating pentest reports with proof-of-concept exploits, or integrating AI pentesting into CI/CD pipelines. Covers the full pentest lifecycle from reconnaissance to reporting using AI orches
You are an expert in E2B, the cloud platform for running AI-generated code in secure sandboxes. You help developers give AI agents the ability to execute code, install packages, read/write files, and run long processes in isolated cloud environments — each sandbox is a lightweight VM that boots in ~150ms with full Linux, filesystem, and networking.
Use when working with icons in any project. Provides CLI for searching 200+ icon libraries (Iconify) and retrieving SVGs. Commands: `better-icons search <query>` to find icons, `better-icons get <id>` to get SVG. Also available as MCP server for AI agents.
Build search applications using Azure AI Search SDK for JavaScript (@azure/search-documents). Use when creating/managing indexes, implementing vector/hybrid search, semantic ranking, or building agentic retrieval with knowledge bases.
Deploy, evaluate, and manage Foundry agents end-to-end: Docker build, ACR push, hosted/prompt agent create, container start, batch eval, prompt optimization, prompt optimizer workflows, agent.yaml, dataset curation from traces. USE FOR: deploy agent to Foundry, hosted agent, create agent, invoke agent, evaluate agent, run batch eval, optimize prompt, improve prompt, prompt optimization, prompt optimizer, improve agent instructions, optimize agent instructions, optimize system prompt, deploy mode
Orchestrate multi-agent teams with defined roles, task lifecycles, handoff protocols, and review workflows. Use when: (1) Setting up a team of 2+ agents with different specializations, (2) Defining task routing and lifecycle (inbox → spec → build → review → done), (3) Creating handoff protocols between agents, (4) Establishing review and quality gates, (5) Managing async communication and artifact sharing between agents.
Multi-agent board meeting protocol for strategic decisions. Runs a structured 6-phase deliberation: context loading, independent C-suite contributions (isolated, no cross-pollination), critic analysis, synthesis, founder review, and decision extraction. Use when the user invokes /cs:board, calls a board meeting, or wants structured multi-perspective executive deliberation on a strategic question.
自主Claude代码循环的模式与架构——从简单的顺序管道到基于RFC的多智能体有向无环图系统。