Agent skill · magnus919
autogen
Expert skill for conversational multi-agent AI with Microsoft AutoGen. AssistantAgent, UserProxyAgent, GroupChat, code execution, nested chats, cancellation tokens, tool integration, and MCP support. Use when building conversation-driven multi-agent systems or comparing agent frameworks.
What it needs
About 3k tokens when loaded.
What this skill does
AutoGen Expert Skill AutoGen (by Microsoft Research) is a framework for conversational multi-agent AI. Unlike LangGraph's explicit graph topology or CrewAI's role-based crews, AutoGen uses agent-to-agent conversations as the orchestration primitive. Agents communicate through structured chat, with built-in patterns for nested conversations, group chat with routing, and code execution. Core Paradigm ⚠️ UserProxyAgent is NOT a human user. It is an automated proxy that can execute code. Despite the name, it runs autonomously unless humaninputmode is set to ALWAYS. Core Principles 1. Conversations are the orchestration primitive. Agents send messages, receive replies, and the conversation structure determines the workflow. 2. UserProxyAgent is a code executor, not a human. Despite the name, it runs autonomously by default. Set humaninputmode="ALWAYS" for actual human-in-the-loop. 3. GroupChat routes between agents. RoundRobinGroupChat cycles fixed-order. SelectorGroupChat uses an LLM to pick the next speaker. 4. Nested chats delegate work. An agent can spawn a sub-conversation between specialist agents and return the result. 5. Docker is the safe code execution mode. Local code execution (LocalCommandLineCodeExecutor) runs LLM-generated code on your machine — use Docker in production. 6. Cancellation tokens stop runaway agents. Always pass CancellationToken for long-running tasks. Where to Start You already have... …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills magnus919/autogen