| name | check-release |
| description | 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. |
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.
