Analysis updated 2026-05-18
Keep a per-task log, status, and notes for every piece of work an AI assistant does with you.
Automatically commit every AI-driven file change to a local git repo so mistakes can be undone.
Save every ad-hoc SQL or Python check the assistant runs to an audit-trail notebook.
Block a new AI coding session from starting on top of an undocumented, messy previous session.
| theboogieman/ai-work-harness | bechsteindigital/claude-shiploop | hannes/quack | |
|---|---|---|---|
| Stars | 3 | 3 | 3 |
| Language | Shell | Shell | Shell |
| Last pushed | — | — | 2024-06-05 |
| Maintenance | — | — | Dormant |
| Setup difficulty | moderate | moderate | moderate |
| Complexity | 3/5 | 4/5 | 4/5 |
| Audience | developer | vibe coder | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires GitHub Copilot's preview custom-agent and hook features, VS Code, git, and a Python 3.12 venv named venv_global with nbformat installed.
AI Work Harness is a local setup that adds structure and record keeping around an AI coding assistant, so the assistant behaves more like a careful colleague than a fast but forgetful one. The project was built after its author burned through forty thousand credits in a month of undisciplined AI use, and it exists so that does not happen again. The core idea is simple. All the working rules live in one markdown file that the AI assistant reads. A handful of small, cheap AI agents handle bookkeeping tasks like logging and note taking, so the more expensive, capable AI model can focus on actual thinking instead of chores. A bash script checks that things are in order before a work session starts, and a local git repository quietly records every change so mistakes can be undone. Setting it up has two parts. First, a sixty second demo script proves the underlying scripts work correctly on your computer, without needing an AI assistant connected at all. Second, an installer sets up a dedicated working folder, called an estate, with the folder structure, a local only git repository, and the small AI agents in place. This step needs a Python environment with a specific package installed beforehand, and it takes about ten minutes. Once set up, working on a task with the AI assistant automatically creates records instead of relying on memory. Every task folder keeps its own log, current status, and notes. Every one-off check you run, whether SQL or Python, gets saved to a notebook that acts as an audit trail. Every file change is automatically committed to the local git history. And a validator script refuses to let a new work session start if the previous one left things in a messy, undocumented state. The project is designed for one person working on one task at a time, currently depends on GitHub Copilot's custom agent and hook features, and works best with VS Code, git, and Python 3.12 already installed. It is released under the MIT license.
A local setup that adds rules, record keeping, and a git safety net around an AI coding assistant so its work stays disciplined and auditable.
Mainly Shell. The stack also includes Shell, Git, Python.
Use freely for any purpose, including commercial use, as long as you keep the copyright notice.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
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