build-your-own-openclaw

Name: build-your-own-openclaw
Author: czl9707

by czl9707

Verified

A step-by-step guide to build your own AI agent.

1,716stars

305forks

Python

Added 3/17/2026

Installation

# Add to your Claude Code skills
git clone https://github.com/czl9707/build-your-own-openclaw

Getting Started

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Security ReportVerified

Last scanned: 4/29/2026

{
  "issues": [],
  "status": "PASSED",
  "scannedAt": "2026-04-29T06:23:40.594Z",
  "semgrepRan": false,
  "npmAuditRan": true,
  "pipAuditRan": true
}

README.md

Frequently Asked Questions

What is build-your-own-openclaw?

build-your-own-openclaw is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by czl9707. A step-by-step guide to build your own AI agent. It has 1,716 GitHub stars.

Is build-your-own-openclaw safe to use?

Yes. build-your-own-openclaw passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.

How do I install build-your-own-openclaw?

Clone the repository with "git clone https://github.com/czl9707/build-your-own-openclaw" and add it to your Claude Code skills directory (see the Installation section above).

What programming language is build-your-own-openclaw written in?

build-your-own-openclaw is primarily written in Python. It is open-source under czl9707 on GitHub, so you can review or fork the full source.

Are there alternatives to build-your-own-openclaw?

Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh build-your-own-openclaw against similar tools.

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Build Your Own OpenClaw

A step-by-step tutorial to build your own AI agent, from a simple chat loop to a lightweight version of OpenClaw.

Overview

18 progressive steps that teach you how to build an minimal version of OpenClaw. Each step includes:

A README.md going through key components and design decision.
A Runnable codebase.

Example Project: pickle-bot - our reference implementation

Tutorial Structure

Phase 1: Capable Single Agent (Steps 0-6)

Build a fully-functional agent that can chat, use tools, learn skills, remember conversations, and access the internet.

00-chat-loop - Just a Chat Loop
01-tools - Give your agent a tool.
02-skills - Extend your agent with SKILL.md
03-persistence - Save your conversations.
04-slash-commands - Direct user control over sessions.
05-compaction - Pack you history and carry on...
06-web-tools - Your Agent want to see the bigger world.

Phase 2: Event-Driven Architecture (Steps 7-10)

Refactor to event-driven architecture for scalability and multi-platform support.

07-event-driven - Expose you agent beyond CLI.
08-config-hot-reload - Edit without restart.
09-channels - Talk to your agent from on your phone.
10-websocket - Want to interact with you agent programatically?

Phase 3: Autonomous & Multi-Agent (Steps 11-15)

Add scheduled tasks, agent collaboration, and intelligent routing.

11-multi-agent-routing - Route right job to right agent.
12-cron-heartbeat - An Agent work while you are sleeping.
13-multi-layer-prompts - More Context, More Context, More Context.
14-post-message-back - Your Agent want to Speak to you.
15-agent-dispatch - Your Agent want friends to work with!

Phase 4: Production & Scale (Steps 16-17)

Features for reliability and long-term memory.

16-concurrency-control - Too many Pickle are running at the same time?
17-memory - Remember me!

How to Use This Tutorial

Configure API Keys

Before running any step, you need to configure your API keys:

Copy the example config:

cp default_workspace/config.example.yaml default_workspace/config.user.yaml

Edit config.user.yaml with your API keys:
- See LiteLLM providers for the full list of supported providers
- Check out Provider Examples for some examples
Just follow each steps, read and try it out.

Contributing

Each step is implemented in a separate session. Feel free to suggest improvements!