🦞 OpenClaw 架構全解析｜AI 助手系統設計深度解說

OpenClaw is a comprehensive AI assistant system architecture featuring a centralized Gateway design that orchestrates Agent Loop operations, memory systems, and skill execution layers. The system demonstrates how to build scalable AI agents through modular components including request routing, agent decision-making loops, persistent memory management, and tool/skill execution capabilities. This deep-dive covers the complete workflow from user input through Gateway to Agent processing and skill invocation.

Key Points

• •Gateway acts as a centralized hub routing all requests to appropriate agents and managing system-wide orchestration
• •Agent Loop implements the core decision-making cycle: perception → reasoning → action → feedback
• •Memory system provides persistent context storage enabling agents to maintain conversation history and learned patterns
• •Skill execution layer abstracts tool invocation allowing agents to call external APIs, databases, and services
• •Modular architecture enables independent scaling of Gateway, Agent, Memory, and Skill components
• •Request routing through Gateway ensures load balancing and request validation before agent processing
• •Agent reasoning uses context from memory to make informed decisions about which skills to invoke
• •Skill abstraction layer decouples agent logic from implementation details of external tools
• •System supports multi-agent coordination through centralized Gateway management
• •Persistent memory enables long-term learning and context preservation across sessions

Workflow Diagram

Concepts