2026年零基础手写AI Agent(最新更新手写OpenClaw)--11 手写Manus之工具相关性过滤

This tutorial covers building AI Agent tools with relevance filtering in the Manus framework (part of OpenClaw). It demonstrates how to implement tool selection mechanisms that filter tools based on relevance to user queries, a critical component for efficient multi-tool AI agents. The content focuses on practical implementation of relevance-based tool routing without external dependencies.

Key Points

• •Implement tool relevance filtering to select appropriate tools based on user query context
• •Use semantic similarity or keyword matching to determine which tools are relevant for a given task
• •Design a tool registry system that stores tool metadata and descriptions for matching
• •Create a filtering mechanism that ranks tools by relevance score before execution
• •Handle edge cases where no relevant tools are found or multiple tools have similar relevance
• •Optimize tool selection to reduce unnecessary API calls and improve response latency
• •Integrate relevance filtering into the agent's decision-making pipeline
• •Test tool filtering with diverse query types to ensure accurate tool selection

Workflow Diagram

Concepts