OpenClaw Learning Manual

🤹🏼 Target Audience

〽️ Learning Objectives

🌈 Introduction

OpenClaw is a powerful and flexible AI agent framework designed to transform AI’s thinking ability into practical operational productivity. It is not just a simple chatbot, but a digital employee capable of running 24/7.


Chapter 1: Cognitive Logic: The Core Logic of OpenClaw

1.1 What is OpenClaw

OpenClaw is an intelligent assistant based on open-source architecture, supporting access to multiple large models, and possessing powerful environmental perception and task execution capabilities.

1.2 Core Advantages of OpenClaw

1.3 Core Architecture

Composed of Gateway, Core Engine (Core), and Communication Channels (Channels), realizing a closed loop from instruction reception to task execution.


Chapter 2: Preparation: Zero-Threshold Deployment Checklist

2.1 Hardware Requirements

No expensive equipment needed; ordinary old computers or entry-level cloud servers can support operation. 4G RAM or above is recommended.

2.2 Software & Accounts


Chapter 3: Deployment: Build Your AI Employee in 30 Minutes

3.1 macOS/Windows Local Deployment

  1. Install Node.js: Download and install from the official website.
  2. Get Source Code: Clone via Git or download the zip package.
  3. Install Dependencies: Run npm install.
  4. Start Configuration: Enter the wizard via command line to configure API Key and communication methods.

3.2 Cloud Server Deployment


Chapter 4: Cases: Efficiency Practice in Daily Scenarios

4.1 File Management

4.2 Email Processing

4.3 Information Research


Chapter 5: Integration: Communication Software Integration

5.1 Integrate Feishu (Lark)

5.2 Integrate Telegram / DingTalk


Chapter 9: Q&A: Common Issues


Chapter 10: Outlook: The Efficiency Revolution of the AI Era

OpenClaw is not just a tool; it represents a new paradigm of collaboration between humans and AI. Through continuous community updates, it will unlock more advanced capabilities such as automated visual processing and more complex long/short-term memory.


Appendix: Common Commands Cheat Sheet