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Contributing to Modelith

Thanks for wanting to help. Modelith is an ontology-anchored, git-native data modeling tool for dbt-core teams, and it grows better with real-world use and feedback.

Ways to help

  • Report first-run friction. If installing or running the quickstart tripped you up, file a "First-run friction" issue. Those reports are high priority.
  • File bugs and feature requests with the issue templates.
  • Improve docs and demos. The demo/ projects and the README are the front door; clarity there helps everyone.
  • Pick up a good-first-issue. Look for the good first issue label.

Development setup

You need Python 3.11+ and uv.

git clone https://github.com/dbose/modelith
cd modelith
uv sync
uv run pytest                    # the full test suite
uv run ruff check packages/      # lint

The CLI is a uv workspace of mdl_* packages under packages/. Running mdl from a uv synced checkout uses your working tree, so edits are picked up without reinstalling.

To work on the canvas or the VS Code extension (Node 20):

cd canvas && npm install && npm run build     # emits into the server static dir
cd vscode && npm install && npm run build     # the extension

Before you open a pull request

  • uv run pytest passes.
  • uv run ruff check packages/ passes.
  • Update the README or docs/ if you changed behavior.
  • Keep the design git-native and stateless: git is the single source of truth, and the server, canvas, and extension are all clients over it. Changes that move model state out of git, or add server-owned state, need discussion first (open an issue).

Commit and PR style

  • Small, focused PRs are easier to review and land faster.
  • Reference the issue you are closing (Closes #123).
  • Write commit messages that explain the why, not just the what.

Questions

Open a Discussion for anything that is not yet a concrete bug or feature. It is the best place to sanity-check an idea before writing code.