colleague

Colleague is a swappable coder-agent harness that turns different model backends into repo workers behind one shared task runtime.

One runtime, many minds.

The problem it solves. AI coder backends are not interchangeable — a local vLLM model, an OpenAI-compatible endpoint, and a hosted assistant each bring their own SDK, controls, and output shape. Colleague is the harness around the model: you point it at a repo task, pick a backend, and it runs the work through that backend’s bounded tool-loop and hands back the same typed result every time. Swap the backend and nothing else about your workflow changes — the caller never has to care which mind ran the task.

Quickstart (30 seconds)

No model and no network required — the mock backend runs the full loop deterministically, so you can see the shape of a task before wiring up a real model:

uv sync
uv run pytest -n auto                            # full suite, offline

# Run your first task through the deterministic mock backend:
uv run colleague work "add a CONTRIBUTING.md stub" --repo . --engine mock --no-pr

# Open the interactive cockpit (the session palette) at a terminal:
uv run…