Skill
assimilate-popular-wor…
This skill should be used when the user asks to "find skills in the wild", "assimilate popular workflows", "discover SKILL.md files in repos", "research…
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Skill
/autogen-setup
Microsoft AutoGen multi-agent configuration for conversational AI systems
Install
$ npx -y skills add a5c-ai/babysitter --skill autogen-setup --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/autogen-setup
Context preview
The summary Claude sees to decide when to auto-load this skill.
Microsoft AutoGen multi-agent configuration for conversational AI systems
SKILL.md
autogen-setup.SKILL.mdname: autogen-setup
description: Microsoft AutoGen multi-agent configuration for conversational AI systems
allowed-tools:
- Read
- Write
- Edit
- Bash
- Glob
- Grep
graph:
domains: [domain:software-engineering]
specializations: [specialization:ai-agents-conversational]
skillAreas: [skill-area:multi-agent-coordination, skill-area:agentic-loops]
roles: [role:ml-engineer, role:backend-engineer]
workflows: [workflow:feature-development, workflow:ml-model-lifecycle]
topics: [topic:design-patterns, topic:api-design]
AutoGen Setup Skill
Capabilities
- Configure AutoGen agents (AssistantAgent, UserProxyAgent)
- Set up agent conversations and group chats
- Implement code execution capabilities
- Design human-in-the-loop patterns
- Configure nested agent architectures
- Implement custom reply functions
Target Processes
- multi-agent-system
- autonomous-task-planning
Implementation Details
Agent Types
1. **AssistantAgent**: LLM-powered assistant 2. **UserProxyAgent**: Human proxy with code execution 3. **GroupChatManager**: Multi-agent orchestration 4. **ConversableAgent**: Base class for custom agents
Configuration Options
- LLM configuration (models, temperatures)
- Code execution settings
- Human input mode
- Max consecutive auto-replies
- Function calling configuration
Patterns
- Two-agent conversations
- Group chats with selection
- Nested conversations
- Teachable agents
Best Practices
- Proper termination conditions
- Safe code execution sandboxing
- Clear agent system messages
- Monitor conversation flow
Dependencies
- pyautogen
Read more
name: autogen-setup description: Microsoft AutoGen multi-agent configuration for conversational AI systems allowed-tools: - Read - Write - Edit - Bash - Glob - Grep graph: domains: [domain:software-engineering] specializations: [specialization:ai-agents-conversational] skillAreas: [skill-area:multi-agent-coordination, skill-area:agentic-loops] roles: [role:ml-engineer, role:backend-engineer] workflows: [workflow:feature-development, workflow:ml-model-lifecycle] topics: [topic:design-patterns, topic:api-design]
AutoGen Setup Skill
Capabilities
- Configure AutoGen agents (AssistantAgent, UserProxyAgent)
- Set up agent conversations and group chats
- Implement code execution capabilities
- Design human-in-the-loop patterns
- Configure nested agent architectures
- Implement custom reply functions
Target Processes
- multi-agent-system
- autonomous-task-planning
Implementation Details
Agent Types
1. **AssistantAgent**: LLM-powered assistant 2. **UserProxyAgent**: Human proxy with code execution 3. **GroupChatManager**: Multi-agent orchestration 4. **ConversableAgent**: Base class for custom agents
Configuration Options
- LLM configuration (models, temperatures)
- Code execution settings
- Human input mode
- Max consecutive auto-replies
- Function calling configuration
Patterns
- Two-agent conversations
- Group chats with selection
- Nested conversations
- Teachable agents
Best Practices
- Proper termination conditions
- Safe code execution sandboxing
- Clear agent system messages
- Monitor conversation flow
Dependencies
- pyautogen
Ships withbabysitter
Enforce obedience on agentic workforces. Manage extremely complex workflows through deterministic, hallucination-free self-orchestration.
Get the whole plugin
Stats
1,788
Stars
106
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Active
Maintenance
JavaScript
Language
MIT
License
10d ago
Last commit
8mo ago
Created
Repo: a5c-ai/babysitter
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