mzpatrick0529-mzyh

Claw Code — Development skill for Claude Code

Development community

Rewriting Project Claw Code — Python rewrite of Claude Code agent harness.

How to install Claw Code

This entry records only its repository, not the path inside it, so there is no exact command to give. Open mzpatrick0529-mzyh/claw-code and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Claw Code does

Rewriting Project Claw Code — Python rewrite of Claude Code agent harness. Forked from instructkr/claw-code.

Alternatives in Development

PaperSpine — PaperSpine is a motivation-driven skill for learning from strong academic papers, building a paper’s central a 5k ★
Asd Ste100 Skill — ASD-STE100 Simplified Technical English rules, repurposed as a Claude Code skill for rewriting ambiguous agent 1.5k ★
Claw Code Agent — Claw Code No Rust No TypeScript Only Python 543 ★

README

Rewriting Project Claw Code

Claw

Better Harness Tools, not merely storing the archive of leaked Claude Code

[!IMPORTANT] **Rust port is now in progress** on the [`dev/rust`](https://github.com/instructkr/claw-code/tree/dev/rust) branch and is expected to be merged into main today. The Rust implementation aims to deliver a faster, memory-safe harness runtime. Stay tuned — this will be the definitive version of the project.

If you find this work useful, consider [sponsoring @instructkr on GitHub](https://github.com/sponsors/instructkr) to support continued open-source harness engineering research.

Backstory

At 4 AM on March 31, 2026, I woke up to my phone blowing up with notifications. The Claude Code source had been exposed, and the entire dev community was in a frenzy. My girlfriend in Korea was genuinely worried I might face legal action from Anthropic just for having the code on my machine — so I did what any engineer would do under pressure: I sat down, ported the core features to Python from scratch, and pushed it before the sun came up.

The whole thing was orchestrated end-to-end using [oh-my-codex (OmX)](https://github.com/Yeachan-Heo/oh-my-codex) by [@bellman_ych](https://x.com/bellman_ych) — a workflow layer built on top of OpenAI's Codex ([@OpenAIDevs](https://x.com/OpenAIDevs)). I used `$team` mode for parallel code review and `$ralph` mode for persistent execution loops with architect-level verification. The entire porting session — from reading the original harness structure to producing a working Python tree with tests — was driven through OmX orchestration.

The result is a clean-room Python rewrite that captu