Clawd Code Python Port

This is a from-scratch Python rewrite of the Claude Code agent harness, built for educational purposes to mirror the tool dispatch, command orchestration, and task execution patterns of the original TypeScript implementation. It gives you a working CLI with commands for inspecting the ported workspace, running parity audits, and exploring the tool and command registries. The architecture is clean: dataclasses for subsystems and modules, a tool registry pattern with JSON schema parameters, and a task wrapper that runs agent loops against a dispatcher. If you want to understand how Claude Code's internals are structured or need a Python agent scaffold with command routing and tool wiring already laid out, this is a readable reference implementation orchestrated end to end with oh-my-codex.

skills.sh installs: 714
GitHub stars: 61
last updated: Jul 14, 2026

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Install

$ npx -y skills add aradotso/trending-skills --skill clawd-code-python-port --agent claude-code

Installs into .claude/skills of the current project.

Files

clawd-code Python Port

Skill by ara.so — Daily 2026 Skills collection.

What This Project Does

clawd-code is an independent Python rewrite of the Claude Code agent harness, built from scratch for educational purposes. It captures the architectural patterns of Claude Code — tool wiring, command dispatch, task orchestration, and agent runtime context — in clean Python, without copying any proprietary TypeScript source.

The project is orchestrated end-to-end using oh-my-codex (OmX), a workflow layer on top of OpenAI Codex. It is not affiliated with or endorsed by Anthropic.

Installation

# Clone the repository
git clone https://github.com/instructkr/clawd-code.git
cd clawd-code

# (Optional but recommended) Create a virtual environment
python3 -m venv .venv
source .venv/bin/activate

# Install dependencies (if a requirements.txt or pyproject.toml is present)
pip install -r requirements.txt
# or
pip install -e .

No API keys are needed for the manifest/summary/CLI commands. If you extend the query engine to call a live model, set your key via environment variable:

SKILL.md on GitHub