Tutorials
Hands-on guides for running OpenClaw AI Agent. Start from scratch and level up step by step.
About OpenClaw
Why You Need OpenClaw: When ChatGPT and Gemini Aren't Enough
You're already using 5 AI tools, but your information is still scattered everywhere. See how OpenClaw helps you connect them all.
Token Economics: Understanding How AI Bills You (So Your Invoice Doesn't Explode)
What are tokens? How do different models charge? Learn to precisely control your AI usage costs and get the most value for your money.
The Full Panorama of AI Tech Evolution: From Transformer to Swarm Intelligence, All in One Read
A 2017 paper changed the world. In 10 minutes, understand the full arc of AI/LLM technological development, and learn why every technology behind OpenClaw exists.
Environment Setup
CLI Beginner's Guide: What Is the Command Line and Why Can't AI Live Without It?
The command-line interface (CLI) is the hands and feet of OpenClaw. Understand how CLI works, common tools, and why it's the most powerful way to operate in the AI era.
Google API Key Complete Guide: Essential for Connecting OpenClaw to Google Drive / Gmail
A step-by-step guide to applying for a Google Cloud API Key โ solving the most common sticking point when connecting OpenClaw to Google services.
Choose Your AI Brain: A Complete Comparison of 4 LLM Options
OpenClaw needs an LLM to work. Understand the differences between ChatGPT subscriptions, OpenRouter, and various APIs to pick the best option for you.
AI Model API Key Guide: OpenAI, Anthropic, Google, OpenRouter โ All in One Place
Step-by-step guide to applying for AI model API Keys. No matter which provider you choose, follow along and get the key that powers OpenClaw.
Installation & Deployment
Why You Shouldn't Install OpenClaw on Native Windows
OpenClaw's core runs on CLI tools and Markdown files. Learn why macOS and Linux are the best habitats for your lobster, and what Windows users should do instead.
Installation Guide: Choose Your Platform
OpenClaw installation entry page. Choose the installation tutorial for your operating system.
Complete WSL Guide: Give Your Windows Linux Superpowers
WSL (Windows Subsystem for Linux) is the best way for Windows users to install OpenClaw. From installation to configuration to daily use โ all in one guide.
Install OpenClaw on macOS: A Complete Step-by-Step Guide
A step-by-step guide to installing OpenClaw on Mac, covering Homebrew, Python environment, dependencies, and your first launch.
Install OpenClaw on Windows: A Complete Step-by-Step Guide
A step-by-step guide to installing OpenClaw on Windows 10/11, covering Python, WSL, dependencies, and your first launch.
Deploy OpenClaw to the Cloud: One-Click Zeabur Deployment + KimiClaw Quick Start
Don't want to deal with local setup? Deploy OpenClaw to Zeabur with one click, or try KimiClaw for an instant cloud AI Agent experience.
Ollama + OpenClaw: No API Key Needed โ Start Chatting with AI in Minutes
No API Key setup required. Use Ollama's free cloud credits to get OpenClaw talking in minutes. Want to run open-source models locally? Full instructions at the end.
Basic Usage
First Launch of OpenClaw: Set Up Your API Key and Hear AI's First Words
Installation done โ now let's bring OpenClaw to life. Follow the setup wizard to initialize everything and get AI to respond within 3 minutes.
Your First Skill: Build Your First Automation Task in 5 Minutes
Your OpenClaw can already chat, but its real power lies in Skills. Follow along and turn a manual task into a one-click automation.
Model Configuration & Switching: Let OpenClaw Auto-Select the Best AI Model
Different tasks call for different models. Learn to configure Providers, model routing, and Fallback mechanisms โ save money and boost efficiency.
Core Features
OpenClaw Skill Complete Guide: Teach AI Repeatable Workflows
Skills are OpenClaw's core feature. Master Skills, and your AI can complete in one click what used to take 30 minutes.
OpenClaw Agent Complete Guide: Build Your AI Double
The Agent is the soul role of OpenClaw โ it understands your intent, auto-selects Skills, and even decides what to do next on its own.
OpenClaw Soul Complete Guide: Give Your Agent Memory, Personality, and Growth
Soul is OpenClaw's most powerful and unique feature. It turns your Agent from just a tool into an AI partner that truly 'knows you.'
MCP Protocol: AI's USB Port โ Plug-and-Play Tools
Model Context Protocol lets AI connect to any tool. Learn how MCP works and why it's the backbone of OpenClaw.
RAG Explained: The Memory Technique That Stops AI from Making Things Up
AI hallucinates and its knowledge goes stale. RAG technology makes AI look up information before answering โ turning 'guessing' into 'citing sources.' Learn how OpenClaw's Memory system uses RAG.
Integration & Automation
Knowledge & Advanced
Prompt Engineering: Making AI Understand You and Give the Answers You Want
Master the core techniques of prompt engineering โ from role-setting to chain-of-thought โ and improve the same model's output quality by 10x.
Build a Personal Knowledge Management (PKM) System with OpenClaw
Say goodbye to information overload. Use OpenClaw to automatically collect, organize, and review knowledge โ make your second brain actually work.
AI Reasoning Techniques Explained: Chain-of-Thought, ReAct, and Tree of Thoughts
How did AI learn to 'think'? From Chain-of-Thought to Tree of Thoughts, discover the techniques that boost AI reasoning by 5x, and how OpenClaw uses them.
Multi-Agent Collaboration and Swarm Intelligence: When AI Learns Teamwork
A single Agent has limited abilities, but a group of Agents working together can solve complex problems. Learn about Multi-Agent collaboration patterns, swarm intelligence concepts, and how OpenClaw implements multi-role coordination.
The Missing Infrastructure of AI Memory: Why Stronger Models Make Agents More Likely to 'Run in Circles'
Memory isn't an add-on feature for AI โ it's the core infrastructure that transforms an Agent from a 'tool' into a 'partner.' This article won't walk you through a paper; instead, it helps you think clearly: if you're designing an AI Agent, what problem is the memory layer actually solving?