agent-architecture-patterns（Agent 架构模式）

Agent Architecture Patterns

This skill provides a comprehensive library of AI Agent architecture patterns to help developers:

• Design single-agent architectures (ReAct, Reflection, Self-Critique, Plan-and-Solve, Tree of Thoughts)
• Design multi-agent collaboration systems (Manager-Worker, Peer-to-Peer, Hierarchical, Market-Based, Pipeline)
• Apply system design principles (separation of concerns, fault tolerance, scalability)
• Implement best practices based on OpenClaw

Patterns

Single-Agent Patterns (5)

1. ReAct - Reasoning + Acting alternation
2. Reflection - Self-reflection and iterative improvement
3. Self-Critique - Self-criticism and error correction
4. Plan-and-Solve - Plan first, then execute
5. Tree of Thoughts - Multi-path exploration

Multi-Agent Patterns (5)

1. Manager-Worker - 1 manager coordinates multiple workers
2. Peer-to-Peer - Equal agents collaborate
3. Hierarchical - Multi-level management structure
4. Market-Based - Task bidding and allocation
5. Pipeline - Sequential multi-stage processing

Usage

Option 1: Consult AI-Agent

Ask questions like:

• "Design a multi-agent code review system"
• "How to implement ReAct pattern?"
• "Which agent collaboration pattern should I use?"

Option 2: Reference Documentation

Browse patterns/ directory for detailed pattern docs.

Option 3: Use Code Examples

Run example code from examples/ directory.

Examples

ReAct Pattern Example

const agent = new ReActAgent({
  tools: [search, calculate],
  maxSteps: 10
});

const answer = await agent.execute("What's the temperature in Beijing today?");

Manager-Worker Pattern Example

const workers = [
  new WorkerAgent('worker-1', ['javascript'], { codeReview: true }),
  new WorkerAgent('worker-2', ['python'], { dataAnalysis: true })
];

const manager = new ManagerAgent(workers);
const result = await manager.coordinate("Review this codebase");

Installation

clawhub install agent-architecture-patterns

Testing

npm test
# Runs 30 test cases for ReAct and Manager-Worker implementations

License

MIT

Author

AI-Agent