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# OpenClaw 从入门到精通 | OpenClaw Guide llms.txt

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llms.txt

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智能体 Harness 工程指南

第一章：Harness 工程概论

1.1 从大语言模型到智能体的快速过渡

1.2 Harness的定义与职责边界

1.3 五大核心子系统总览

1.4 Harness为什么比模型更重要

1.5 MiniHarness项目介绍

本章小结

第二章：Harness 架构全景

2.1 通用参考架构

2.2 执行层的详细设计

2.3 安全层与可观测性层

2.4 层间接口设计

2.5 MiniHarness脚手架搭建

本章小结

第三章：设计原则与方法论

3.1 约束优先原则

3.2 可验证性原则

3.3 渐进信任原则

3.4 故障假设原则

3.5 智能体工学原则

本章小结

第四章：运行时引擎

4.1 智能体循环的工程实现

4.2 消息类型系统与状态管理

4.3 流式处理与事件驱动架构

4.4 错误处理与故障恢复

4.5 长时任务的漂移检测与纠正

4.6 Token预算与上下文动态管理

4.7 实战：MiniHarness 运行时实现

4.8 实时控制平面

本章小结

第五章：工具层设计

5.1 工具抽象接口设计

5.2 工具执行流水线

5.3 工具类型体系

5.4 动态发现与加载

5.5 实战：MiniHarness 工具层实现

本章小结

第六章：记忆与上下文子系统

6.1 Harness中的记忆系统工程设计

6.2 可写入式智能体记忆构建

6.3 上下文组装引擎与缓存策略

6.4 记忆整合与自动化维护

6.5 MiniHarness 记忆系统架构

本章小结

第七章：模型集成与输出治理

7.1 模型抽象层设计

7.2 结构化输出解析与校验

7.3 输出质量门控与过滤

7.4 幻觉检测与工具调用验证

7.5 推理预算与思考过程管理

7.6 实战：实现 MiniHarness 输出治理层

本章小结

第八章：任务编排与工作流引擎

8.1 复杂任务分解与依赖建模

8.2 状态机与工作流引擎

8.3 Harness中的多智能体编排实现

8.4 智能体间通信

8.5 实战：为MiniHarness添加编排引擎

本章小结

第九章：MCP 与工具生态集成

9.1 Harness中的MCP集成设计

9.2 传输层：stdio 与 Streamable HTTP

9.3 MCP服务端开发

9.4 Harness中的MCP集成模式

9.5 实战：为MiniHarness集成MCP

本章小结

第十章：生产级 Harness 构建

10.1 系统提示词工程

10.2 插件与扩展体系设计

10.3 性能优化与成本控制

10.4 配置管理与特性门控

10.5 实战：MiniHarness 生产化加固

本章小结

第十一章：容错与可靠性工程

11.1 可观测性体系

11.2 反馈循环与人机协同设计

11.3 容错模式与系统级恢复

11.4 幻觉防护的工程实践

11.5 实战：为 MiniHarness 添加可靠性保障

本章小结

第十二章：Harness 安全体系

12.1 Harness 层安全威胁模型

12.2 权限系统与沙箱设计

12.3 工具调用护栏

12.4 路径校验与注入防护

12.5 实战：MiniHarness 安全层集成

本章小结

第十三章：评估与质量保障

13.1 Harness 评估方法论

13.2 端到端测试策略

13.3 基准测试

13.4 持续评估与监控

13.5 实战：MiniHarness 完整测试

本章小结

第十四章：Harness 工程的未来

14.1 智能体原生应用

14.2 标准化演进

14.3 开放问题

本章小结

附录

附录 A：术语表

附录 B：参考文献

附录 C：推荐资源

附录 D：MiniHarness 实战项目

## What is OpenClaw 从入门到精通 | OpenClaw Guide's llms.txt?

OpenClaw 从入门到精通 | OpenClaw Guide publishes an `/llms.txt` file that provides AI systems with a structured index of its documentation. It follows the [llms.txt specification](https://llmstxt.org), organizing links to guides, API references, and tutorials under section headings so that LLMs like ChatGPT, Claude, and Gemini can quickly understand what OpenClaw 从入门到精通 | OpenClaw Guide offers and where to find details.

Pass

Spec

1

Sections

106

Links

16.6 KB

Size

~3.8k

Tokens

Sections: Docs

## Add OpenClaw 从入门到精通 | OpenClaw Guide Docs to Your AI Assistant

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1. 1

   Open any chat or composer panel
2. 2

   Type @Docs and select "Add new doc"
3. 3

   Paste the URL: https://yeasy.gitbook.io/llms.txt
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   Reference @Docs in chat when asking about OpenClaw 从入门到精通 | OpenClaw Guide

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## Spec Compliance 4 notes

## Frequently Asked Questions

Where is OpenClaw 从入门到精通 | OpenClaw Guide's llms.txt file?

OpenClaw 从入门到精通 | OpenClaw Guide publishes its llms.txt at https://yeasy.gitbook.io/llms.txt. This file provides a structured, markdown-formatted index of OpenClaw 从入门到精通 | OpenClaw Guide's documentation that AI systems can consume to understand the project's APIs, guides, and references.

How do I use OpenClaw 从入门到精通 | OpenClaw Guide's llms.txt with AI coding assistants?

Copy the llms.txt content and paste it into your AI assistant (Cursor, Windsurf, Claude, ChatGPT) as context. This gives the AI an accurate map of OpenClaw 从入门到精通 | OpenClaw Guide's documentation so it can provide better code suggestions and answers about OpenClaw 从入门到精通 | OpenClaw Guide.

What does OpenClaw 从入门到精通 | OpenClaw Guide's llms.txt contain?

OpenClaw 从入门到精通 | OpenClaw Guide's llms.txt contains 1 sections and 106 documentation links in 16.6 KB (~3.8k tokens). Key sections include Docs.

How many tokens does OpenClaw 从入门到精通 | OpenClaw Guide's llms.txt use?

The concise llms.txt index is approximately 3.8k tokens (16.6 KB). Most AI assistants can fit this within their context window. For the full expanded documentation, look for an llms-full.txt variant which embeds all content inline.

What is OpenClaw 从入门到精通 | OpenClaw Guide?

最新Docker容器技术，从真实案例中学习最佳实践！| Learn and understand Docker&Container technologies, with real DevOps practice!. OpenClaw 从入门到精通 | OpenClaw Guide's llms.txt file helps AI systems understand this by providing a structured overview of its documentation, making it easier for developers to get accurate AI-assisted help when working with OpenClaw 从入门到精通 | OpenClaw Guide.

Can I generate an llms.txt for my own project?

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