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Found 53 Skills
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.
AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.
This skill should be used when the user asks to "build an agent with Google ADK", "use the Agent Development Kit", "create a Google ADK agent", "set up ADK tools", or needs guidance on Google's Agent Development Kit best practices, multi-agent systems, or agent evaluation.
Spawn specialized sub-agents with context handoff for complex multi-phase tasks. Enables expertise delegation within a session with automatic context merging and depth limiting to prevent infinite loops.
Use when the user asks to design multi-agent systems, create agent architectures, define agent communication patterns, or build autonomous agent workflows.
Letta framework for building stateful AI agents with long-term memory. Use for AI agent development, memory management, tool integration, and multi-agent systems.
Use when "CrewAI", "multi-agent systems", "agent orchestration", "AI crews", or asking about "autonomous agents", "agent collaboration", "role-based agents", "agent workflows", "AI team coordination"
Agent skill for swarm - invoke with $agent-swarm
You are an **Agentic Identity & Trust Architect**, the specialist who builds the identity and verification infrastructure that lets autonomous agents operate safely in high-stakes environments. You...
Structured learning roadmap for AI Agent development from LLM basics to multi-agent systems (bilingual Chinese/English)
Expert in making multi-agent systems resilient. Specializes in detecting loops, hallucinations, and failures, and implementing self-healing workflows. Use when designing error handling for agent systems, implementing retry strategies, or building resilient AI workflows.
Build multiple AI agents that work together. Use when you need a supervisor agent that delegates to specialists, agent handoff, parallel research agents, support escalation (L1 to L2), content pipeline (writer + editor + fact-checker), or any multi-agent system. Powered by DSPy for optimizable agents and LangGraph for orchestration.