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check-release

Testing & Quality
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Verifies that a TorchJD release was published correctly by checking the docs site, installing from PyPI, and smoke-testing newly added classes. Use after a release has been merged and published.

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Source SKILL.md: https://github.com/SimplexLab/TorchJD/blob/HEAD/skills/check-release/SKILL.md

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Copying this prompt does not install or run the skill. Review third-party files before use. Codex skill guide

Check TorchJD Release

This skill verifies that a release is live and correct after it has been published.

For agents: invoke as /check-release X.Y.Z (e.g. /check-release 0.16.0). If no version is provided, read the current version from pyproject.toml.

Instructions

Step 1: Determine the version

Read pyproject.toml to find the version field under [project]. Use the version provided as an argument, or the one from pyproject.toml if none is given.

Step 2: Identify newly added classes

Read CHANGELOG.md and find the ## [X.Y.Z] section. Extract the names of any newly added public classes, functions, or methods listed under ### Added. You will use these in later steps.

Step 3: Check the docs site

Fetch https://torchjd.org.

  • Verify that the versions dropdown (or switcher) includes vX.Y.Z as an entry.
  • Verify that the stable entry is present.

If the version entry is missing, report it and stop — the rest of the checks depend on the docs being live.

Step 4: Verify the new-version docs contain the newly added classes

For each newly added class or function identified in Step 2, fetch its expected docs page under https://torchjd.org/vX.Y.Z/. Use the URL patterns from similar existing classes found in README.md or by browsing the stable docs (https://torchjd.org/stable/) to infer the correct path (e.g. https://torchjd.org/vX.Y.Z/docs/aggregation, https://torchjd.org/vX.Y.Z/docs/scalarization, etc.).

Confirm that each new class/function name appears on the fetched page.

Step 5: Verify the stable docs also reflect the new version

Fetch the same doc pages under https://torchjd.org/stable/ and confirm the newly added classes/functions appear there too (i.e. stable points to the new release).

Step 6: Install torchjd from PyPI in a temp environment

Run the following commands to create an isolated install:

cd /tmp && mkdir -p test_torchjd_install && cd test_torchjd_install
uv venv && uv pip install torchjd

Verify the installed version matches X.Y.Z:

cd /tmp/test_torchjd_install && uv pip show torchjd

If the version is wrong, you may need to install with --no-cache.

Step 7: Smoke-test the newly added classes

Write a minimal Python script /tmp/test_torchjd_install/smoke_test.py that:

  • Imports each newly added class or function by its fully-qualified name from torchjd.
  • Instantiates or calls each one with a minimal valid input (e.g. a small torch.Tensor, a dummy preference vector, or no arguments if the class takes none).
  • Does NOT assert correctness of values — only that the code runs without raising an exception.

Use the existing test suite under tests/ or the docs pages fetched in Step 4 as a reference for correct import paths and minimal usage patterns.

Run the script:

cd /tmp/test_torchjd_install && uv run python smoke_test.py

Report the result. If it crashes, show the traceback.

Step 8: Clean up

rm -rf /tmp/test_torchjd_install

Step 9: Report

Summarize what was verified:

  • Docs site: version dropdown ✓/✗, new-version page ✓/✗, stable page ✓/✗
  • PyPI install: version matches ✓/✗
  • Smoke test: each newly added class ✓/✗ (list them)

If everything passes, the release is confirmed good. If anything failed, describe what needs attention.