shareAI-lab/learn-claude-code
Bash is all you need - A nano claude code–like 「agent harness」, built from 0 to 1
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
The project lists 55 contributors on GitHub.
Peaked at #4 in the weekly ranking the week of Mar 15, its best in the past year.
Use Cases & Benefits
- Teaches how to build AI coding agents from scratch using progressive Python tutorials that incrementally add agent capabilities.
- Provides a minimal, clear, and educational approach to understanding AI agents by implementing core concepts step-by-step in under 1100 lines.
- Use for learning the fundamentals of AI agent design through hands-on coding of tools, planning, subagents, and skills mechanisms.
- Use for developing custom AI agents by forking and extending modular agent versions tailored to specific tasks or domains.
- Use for educators and students seeking a structured tutorial to demystify complex AI agent architectures with practical code examples.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
MIT
Permissive: commercial use, modification and redistribution are allowed with attribution.
Community files
- README: present
- Contributing guide: present
Watch-outs
- No GitHub releases; pin a commit or tag instead of a release.
General guidance from repository metadata, not legal advice. How we score
From the README
Disclaimer: This is an independent educational project by shareAI Lab. It is not affiliated with, endorsed by, or sponsored by Anthropic. "Claude Code" is a trademark of Anthropic.
Learn how modern AI agents work by building one from scratch.
We created this repository out of admiration for Claude Code - what we believe to be the most capable AI coding agent in the world. Initially, we attempted to reverse-engineer its design through behavioral observation and speculation. The analysis we published was riddled with inaccuracies, unfounded guesses, and technical errors. We deeply apologize to the Claude Code team and anyone who was misled by that content.
Over the past six months, through building and iterating on real agent systems, our understanding of "what makes a true AI agent" has been fundamentally reshaped. We'd like to share these insights with you. All previous speculative content has been removed and replaced with original educational material.
Works with Kode CLI, Claude Code, Cursor, and any agent supporting the Agent Skills Spec.
A progressive tutorial that demystifies AI coding agents like Kode, Claude Code, and Cursor Agent.
5 versions, ~1100 lines total, each adding one concept:
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+6,206 stars over 88 days across 8 snapshot days; best day +21 on Sep 9.
Forks
12.8K+839
Open issues
58-10
Compared with peers in AI Agents
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 8, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| morluto/rea | 450.0K | +22.9K | 75 | 16 days ago |
| vercel-labs/agent-desktop | 21.4K | +8.7K | 75 | 5 days ago |
| milind-soni/OpenMausBot | 20.6K | +8.4K | 75 | today |
| stablyai/orca | 121.4K | +6.7K | 75 | today |
| thedotmack/claude-mem | 115.8K | +4.7K | 75 | today |
| shareAI-lab/learn-claude-code | 79.9K | — | 40 | — |
| Category median | 115.8K | +8.4K | 75 | — |
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