learn-claude-code
A teaching repo that walks you through building a simple Claude Code-style agent harness from scratch.
- Stars
- 79.7k
- Forks
- 12.8k
- Licence
- MIT
- Language
- Python
- Last update
- 10 days ago
- Type
- Learning resource
What it is
This repository is a tutorial for building the "harness" around an AI model: the tools, context management, and permission rules that let a model act as a coding agent. It is modeled loosely on Claude Code and is meant to show how such a system is put together from the ground up. The README argues that the model supplies the intelligence while the surrounding code supplies the environment.
- Read the harness design sections to learn how tools, knowledge, and permissions fit together
- Follow the tutorial code to build a minimal agent loop with tool calls
- Use the listed Claude Code components as a checklist for your own agent design
- Study how context compaction and subagent spawning are described as harness features
Great for
- Developers who want to understand how coding agents like Claude Code are structured
- Engineers building their own agent tooling who want clear design patterns
- Students learning about LLM agents from a hands-on, code-first angle
- Readers who want a conceptual framing of agents versus scripted workflows
Not ideal for
- People looking for a ready-to-use coding assistant, since this is a teaching project rather than a finished product
- Non-programmers, because the material assumes comfort reading Python and agent concepts
- Anyone expecting neutral comparisons, since the README takes a strong opinion against workflow-builder style agent platforms
How to get it
- 1
Clone and build from source
You'll need: Python
Clone the repository
git clone https://github.com/shareAI-lab/learn-claude-code - 2
Run it
- Clone the repository and open it in your editor
- Read the README sections on harness design to understand the core concepts
- Work through the tutorial code in the repository, starting from the basics
- Check the homepage at learn.shareai.run for the guided version of the material
- 3
Get the most out of it
- Read the harness components list and map each one to a piece of the tutorial code
- Pair the reading with the homepage at learn.shareai.run for a guided path
- Compare the README's design claims against your own agent experiments
- Read the Chinese and Japanese READMEs if you prefer those languages
Downloads
Strengths
- Free, MIT-licensed, and openly readable code
- Breaks a complex agent system into explainable parts
- Large community interest, with a very high star count shown in the metadata
Trade-offs
- The README is a long opinionated essay, so the practical steps are harder to find
- It is a teaching project and does not claim to be production-ready
- The README is truncated here, so the exact tutorial structure and setup details are not confirmed
How it compares
| Project | Stars | Type | Level | Updated | Best for |
|---|---|---|---|---|---|
| learn-claude-code (this) | 79.7k | Learning resource | intermediate | 10 days ago | Developers who want to understand how coding agents like Claude Code are structured |
| langchain | 149k | Framework | intermediate | 4 days ago | Python developers building LLM-powered applications |
| OpenHands | 92.5k | App | intermediate | 4 days ago | Developers who want coding agents running on a server while their laptop is off |
| hermes-agent | 260k | AI model / agent | intermediate | 4 days ago | Developers who want a personal agent they can host on their own server or machine |
| ai-berkshire | 17k | AI model / agent | intermediate | 4 days ago | Chinese-speaking investors who want a structured value investing checklist applied to specific companies |
| claude-code-best-practice | 68.5k | Learning resource | beginner | 4 days ago | Developers who are new to Claude Code and want an organized overview of its features |
Stats synced from GitHub. The assessment above was drafted with AI from the project's README on 2026-10-29 and may miss recent changes — check the README before relying on a command. MIT licence: free to use, modify and distribute, including commercially, as long as you keep the copyright notice.