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Harneloop

Helps an AI agent learn from what went wrong: inspect real results, trace the mistake and keep only harness changes a test supports.

CodingCLIPackaged

Installation

Install from PyPI ↓Source repository ↗

Version 0.0.2 · The harneloop command-line tool as a Python package. The repository also holds docs, examples, tests and translations that are not needed to use it.

  1. Install the command

    Install it as an isolated tool with uv, then run the doctor check. You can also use python -m pip install harneloop in your own Python 3.11+ environment.

    Harneloop on PyPI ↗
    uv tool install harneloop
harneloop doctor

  2. Give your agent the repository

    Harneloop is meant to be driven by an agent with file and terminal access. Ask it to read the README and docs/agent-onboarding.md, then use Harneloop to create a harness unit for the task you want it to get better at.

    Agent quick start prompt ↗
    harneloop onboard --format json

  3. Or start it yourself

    harneloop setup opens a guided menu that creates and registers a harness unit. After that you can check any unit by name from any folder.

    harneloop setup
harneloop units list

Manual setup

  • Python 3.11 or newer and git. uv is recommended for an isolated install; if uv says its tool folder is not on PATH, run uv tool update-shell and open a new terminal.
  • You bring the task and the environment it runs in. Harneloop does not discover endpoints, tools, screenshots or output paths for you; the agent maps them into the harness unit.

Additional notes

  • Public alpha. The core loop works; the first published case study is Blender scene construction with ViperMesh.
  • It changes the harness around the model (instructions, tools, context and checks), not the model itself. A proposed change becomes the working version only after a test supports it.