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Cute Verify (PyTorch)
Verify changes to the Helion CuTe backend by running both test suites, lint, and a code review subagent — then fix any issues found.
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Installer dans ton projet
$ curl -fsSL https://arboristhree.xyz/cli/install-skill.mjs -o /tmp/arboris-install-skill.mjs && node /tmp/arboris-install-skill.mjs cute-verify__pytorch-helion__claude-skills-5b17ace4dee2PyTorch
pytorch/helion
Contenu à copier
--- name: cute-verify description: Verify changes to the Helion CuTe backend by running both test suites, lint, and a code review subagent — then fix any issues found. metadata: origin: PyTorch --- Run all four checks, then fix any issues: 1. **Lint** — `./lint.sh` (Ruff + Pyrefly). 2. **Default test suite** — `pytest test/ -q --tb=line`. 3. **CuTe test suite** — `HELION_BACKEND=cute pytest test/ -q --tb=line`. 4. **Code review** — spawn an Opus-class `general-purpose` subagent with the diff (`git diff HEAD~` covers the last commit plus staged and unstaged changes, but not untracked files; pick the right scope for the situation). **Parallelism:** Running lint and the code-review subagent in parallel with the test suites is fine. Each pytest suite picks enough xdist workers to fill the GPU it sees, so **never run the two suites on the same GPU** — twice the workers on one GPU causes OOMs and flaky failures. Run them in parallel on two different idle GPUs (`CUDA_VISIBLE_DEVICES=...`), or sequentially if only one GPU is free. **Review subagent prompt** (use `subagent_type: general-purpose`, `model: opus`): > Review `git diff HEAD~` in `<repo root>`. Focus on: > - **Correctness:** wrong logic, missed edge cases, broken invariants. > - **Simplification:** redundant code, layers that could collapse, premature abstractions. > - **Hacky things:** ad-hoc workarounds, type-casts that hide bugs, magic constants without comments, stub APIs that aren't really plumbed. > - **Disabled / regressed coverage:** tests that were deleted or `@skip`ed without an equivalent replacement; functionality that silently lost a code path (e.g. an `if` branch removed without checking callers). > > Report concrete `file:line` issues. Under 400 words. Say "LGTM" plainly if clean. If any check fails, fix the underlying issue (don't suppress it) and re-run only that check. Repeat until all four are clean. Final report: | Check | Result | | ----- | ------ | | ./lint.sh | clean / N issues fixed | | pytest (default) | <pass>/<skip> | | pytest (cute) | <pass>/<skip>/<xfail> | | code review | LGTM / <N> nits applied | Notes: - Don't pass `HELION_AUTOTUNE_EFFORT=none` to a full suite run; it changes execution paths and breaks tests. Use it only for targeted local iteration. - Use `pytest -ra` if a skip count looks suspicious — it prints skip reasons.
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Ce que fait Cute Verify (PyTorch)
Don't pass `HELION_AUTOTUNE_EFFORT=none` to a full suite run; it changes execution paths and breaks tests. Use it only for targeted local iteration.
Use `pytest -ra` if a skip count looks suspicious — it prints skip reasons.
Comment utiliser Cute Verify (PyTorch)
1
Copie le prompt
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2
L'agent installe le skill
Il ajoute le SKILL.md et ses ressources à ton projet.
3
Activation automatique
Le skill s'active dès que le contexte correspond.
Déclencheurs pour Cute Verify (PyTorch)
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