> For the complete documentation index, see [llms.txt](https://yeasy.gitbook.io/openclaw_guide/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://yeasy.gitbook.io/openclaw_guide/readme_en.md).

# OpenClaw: Beginner to Expert

[中文文档](/openclaw_guide/readme.md)

## OpenClaw: Beginner to Expert

[![License: CC BY 4.0](https://img.shields.io/badge/License-CC%20BY%204.0-lightgrey.svg)](https://creativecommons.org/licenses/by/4.0/) [![GitHub stars](https://img.shields.io/github/stars/yeasy/openclaw_guide?style=social)](https://github.com/yeasy/openclaw_guide) [![Release](https://img.shields.io/github/release/yeasy/openclaw_guide.svg)](https://github.com/yeasy/openclaw_guide/releases) [![Online Reading](https://img.shields.io/badge/Read_Online-GitBook-brightgreen)](https://yeasy.gitbook.io/openclaw_guide) [![PDF](https://img.shields.io/badge/PDF-Download-orange)](https://github.com/yeasy/openclaw_guide/releases/latest)

> [**OpenClaw**](https://github.com/openclaw/openclaw) **is an open-source, local-first personal AI assistant**, created by Peter Steinberger. This book provides a comprehensive guide from getting started to production deployment, with deep dives into the underlying mechanisms and implementation principles.

<img src="/files/yteei2Bh6wNwrk2oMS5z" alt="OpenClaw Guide Cover" width="300">

### Highlights

> Note: this English page is currently an overview. The full chapter-by-chapter content is maintained in Chinese; for complete reading, use the Chinese README and table of contents.

* **Hands-on**: Build a minimal working loop from scratch, with ready-to-use configuration templates
* **Deep Dives**: Detailed analysis of Gateway, Agent Loop, tool system, sessions and memory
* **Production-Ready**: Focus on reliability, security hardening, monitoring and troubleshooting

### Target Audience & Prerequisites

* **Target Audience**: Individual users interested in AI agents, AI application developers, LLM engineers, system architects, etc.
* **Prerequisites**: Basic backend development familiarity is expected, such as Node.js or Python fundamentals. If you are new to LLMs and AI agents, see [AI Beginner Guide](https://github.com/yeasy/ai_beginner_guide) and [Agentic AI Guide](https://github.com/yeasy/agentic_ai_guide).

### Book Structure

| Part                            | Chapters | Overview                                                                                                                                                                                      |
| ------------------------------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Part 1: Getting Started         | Ch 1–4   | Overview, setup, first conversation, configuration & model access                                                                                                                             |
| Part 2: Advanced Usage          | Ch 5–8   | Tools & skills, context memory, multi-agent collaboration, automation & ops                                                                                                                   |
| Part 3: Internals & Engineering | Ch 9–12  | Gateway protocol, Agent Loop internals, reliability, plugin extensions                                                                                                                        |
| Part 4: Practice & Optimization | Ch 13–16 | Case studies, performance & cost optimization, troubleshooting, AI ecosystem integration                                                                                                      |
| Appendix                        | —        | Glossary, config templates, troubleshooting checklist, API reference, command cheatsheet, version mapping, further reading, environment self-check tool, naming history, volatile facts table |

### How to Read

#### Online

* [GitBook Online](https://yeasy.gitbook.io/openclaw_guide/)
* [Chinese Full Edition](/openclaw_guide/readme.md)

#### Local Preview

This repository uses mdPress for building. For local preview:

```bash
brew tap yeasy/tap && brew install mdpress
mdpress serve
```

Other Markdown previewers can be used as auxiliary tools, but they are not the standard build chain for this repository.

### 5-Minute Quick Start

New to OpenClaw? Just three steps:

1. **Install** (1 min): `curl -fsSL https://openclaw.ai/install.sh | bash -s -- --no-onboard` (locked-down environments should download and inspect the script first, or use the official manual/npm path)
2. **Initialize** (2 min): `openclaw onboard --install-daemon` → follow the wizard to configure your model API key and install the background service
3. **Chat** (2 min): Run `openclaw dashboard`, type "hello" in the Control UI chat, receive an AI response — you're done! 🎉

See [Chapter 2: Setup](/openclaw_guide/di-yi-bu-fen-ji-chu-ru-men/02_setup.md) and [Chapter 3: First Conversation](/openclaw_guide/di-yi-bu-fen-ji-chu-ru-men/03_minimal_loop.md).

### Learning Paths

Different readers can choose their path:

| Role            | Core Chapters  | Est. Time  | What You'll Achieve                                              |
| --------------- | -------------- | ---------- | ---------------------------------------------------------------- |
| Individual User | 1→2→3→5→7      | 3-4 hours  | Build a personal WhatsApp/Telegram AI assistant                  |
| App Developer   | 1-7→12         | 8-10 hours | Develop custom tools, skills and multi-agent systems             |
| Ops Engineer    | 2→3→8→11→14→15 | 6-8 hours  | Production deployment, security hardening & troubleshooting      |
| Architect       | 1→9→10→12→16   | 6-8 hours  | Understand internals, design enterprise-grade agent architecture |

### Related Books

This book is part of an AI technology series:

| Book                                                                            | Relationship                                      |
| ------------------------------------------------------------------------------- | ------------------------------------------------- |
| [AI Beginner Guide](https://github.com/yeasy/ai_beginner_guide)                 | Zero-to-one AI introduction                       |
| [Prompt Engineering Guide](https://github.com/yeasy/prompt_engineering_guide)   | Agent prompt design fundamentals                  |
| [Context Engineering Guide](https://github.com/yeasy/context_engineering_guide) | Context management & memory architecture          |
| [Claude Guide](https://github.com/yeasy/claude_guide)                           | Claude MCP protocol, tools & Agentic Coding       |
| [Agentic AI Guide](https://github.com/yeasy/agentic_ai_guide)                   | General agent architecture & multi-agent patterns |
| [AI Security Guide](https://github.com/yeasy/ai_security_guide)                 | Agent security design & attack/defense practices  |
| [LLM Internals](https://github.com/yeasy/llm_internals)                         | Deep dive into LLM architecture                   |

### Contributing

Welcome to submit [Issues](https://github.com/yeasy/openclaw_guide/issues) or [PRs](https://github.com/yeasy/openclaw_guide/pulls). Especially welcome: typo fixes, broken link repairs, case study additions, and reusable templates.

### License

This book is licensed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).
