Contributing¶
Prerequisites • Developing and testing • Building from source • Developing goose-plugins • Running ai-exchange from source • Evaluations • Conventional Commits
We welcome Pull Requests for general contributions. If you have a larger new feature or any questions on how to develop a fix, we recommend you open an issue before starting.
Prerequisites¶
We provide a shortcut to standard commands using just in our justfile
.
Goose uses uv for dependency management, and formats with ruff - install UV first: https://pypi.org/project/uv/
Developing and testing¶
Now that you have a local environment, you can make edits and run our tests.
Creating plugins¶
Goose is highly configurable through plugins - it reads in modules that its dependencies install (e.g.goose-plugins
) and uses those that start with certain prefixes (e.g. goose.toolkit
) to inject their functionality. For example, you will note that Goose's CLI is actually merged with additional CLI methods that are exported from goose-plugins
.
If you are building a net new feature, you should try to fit it inside a plugin. Goose and goose-plugins
both support plugins, but there's an important difference in how contributions to each are reviewed. Use the guidelines below to decide where to contribute:
When to Add to Goose:
Plugins added directly to Goose are subject to rigorous review. This is because they are part of the core system and need to meet higher standards for stability, performance, and maintainability, often being validated through benchmarking.
When to Add to goose-plugins
:
Plugins in goose-plugins
undergo less detailed reviews and are more modular or experimental. They can prove their value through usage or iteration over time and may be eventually moved over to Goose.
To see how to add a toolkit, see the toolkits documentation.
Running tests¶
or, as a shortcut,
Building from source¶
If you want to develop features on goose
:
- Clone Goose:
- Get
uv
withbrew install uv
- Set up your Python virtualenv:
- Run the
source
command that follows theuv venv
command to activate the virtualenv. - Run Goose:
Running from source¶
When you build from source you may want to run it from elsewhere.
- Run
uv sync
as above - Run
export goose_dev=`uv run which goose`
- You can use that from anywhere in your system, for example
cd ~/ && $goose_dev session start
, or from your path if you like (advanced users only) to be running the latest.
Developing goose-plugins¶
- Clone the
goose-plugins
repo:
- Follow the steps for creating a virtualenv in the
goose
section above - Install
goose-plugins
ingoose
. This means any changes togoose-plugins
in this folder will immediately be reflected ingoose
:
- Make your changes in
goose-plugins
, add the toolkit to theprofiles.yaml
file and runuv run goose session --start
to see them in action.
Running ai-exchange from source¶
goose depends heavily on the ai-exchange
project, you can clone that repo and then work on both by running:
then when you run goose with uv run goose session start
it will be running it all from source.
Evaluations¶
Given that so much of Goose involves interactions with LLMs, our unit tests only go so far to confirming things work as intended.
We're currently developing a suite of evaluations, to make it easier to make improvements to Goose more confidently.
In the meantime, we typically incubate any new additions that change the behavior of the Goose through opt-in plugins - Toolkit
s, Moderator
s, and Provider
s. We welcome contributions of plugins that add new capabilities to goose. We recommend sending in several examples of the new capabilities in action with your pull request.
Additions to the developer toolkit change the core performance, and so will need to be measured carefully.
Conventional Commits¶
This project follows the Conventional Commits specification for PR titles. Conventional Commits make it easier to understand the history of a project and facilitate automation around versioning and changelog generation.