self-review

作成者: huggingface

Use before opening a PR, or whenever asked to self-review a diffusers contribution. Applies the same rubric as the `@claude` CI (checks the diff against…

npx skills add https://github.com/huggingface/diffusers --skill self-review

Self-review

Runs the same rubric as the @claude CI reviewer, so you catch issues before a maintainer does — but over your whole PR diff. (The CI scopes itself to src/diffusers/, tests/, and .ai/; for your own PR, also review your docs and scripts.) You're already on the branch with the conventions loaded, so: get the diff → review it against the rubric → report → iterate with the contributor until it's ready, then remind them to share the final notes on the PR.

1. Get the diff

git diff main...HEAD          # use your target branch if not main

If the branch trails main and the diff looks polluted with unrelated merged files, scope to your own commits: git log main..HEAD --oneline, then git show <commit>.

2. Read the rubric

.ai/review-rules.md is the canonical rubric (the CI pins it from main) — read it and review against it; don't rely on a remembered copy. For the areas you touched, also read .ai/models.md, .ai/pipelines.md, or .ai/modular.md.

3. Report

  • Blocking issues — numbered. Each: title → explanation → file.py:line → impact. Cite the rule, e.g. Per .ai/models.md: "…only keep the inference path."
  • Non-blocking issues — same format, lower severity.
  • Dead code (advisory) — a table: path:line · Likely-dead / Used · reason.
  • Summary — short synthesis and a verdict (READY / NEEDS CHANGES), spelling out:
    • Fix before submitting — all blocking issues, and remove the flagged dead code.
    • Leave for the actual review — non-blocking issues that aren't obviously correct; raise these with the reviewer rather than guessing at them now.

Report only — do not edit files. Be concrete, cite the rule, review the whole diff, and don't invent issues or flag pure style.

4. Iterate until ready, then share

Expect several rounds: the contributor addresses findings, you review again. Keep working with them to fix as much as possible until the verdict is READY — the Leave for the actual review items are the only ones that should reach the reviewer unresolved. End the final round's report by reminding the contributor to share it on the PR (description or a comment) — it saves the reviewer a few rounds of back-and-forth. Never commit the notes as part of the diff.

huggingfaceのその他のスキル

cpu-kernels
huggingface
C++ CPUカーネルをSIMDイントリンシクス(AVX2/AVX512)を用いて記述、最適化、ベンチマークするためのガイダンスを提供します。Hugging Faceカーネルエコシステム向けです。含まれるもの…
official
generate-openenv-env
huggingface
具体的なユースケース(例:「ライブラリtextarena用のenvを生成する」)からOpenEnv環境を生成します。新しい環境の設計や実装を求められた際に使用します。
official
hf-mcp
huggingface
Hugging Face HubをMCPサーバーツール経由で利用します。モデル、データセット、Spaces、論文を検索できます。リポジトリの詳細を取得し、ドキュメントを取得し、計算ジョブを実行し、Gradioを使用します…
official
trl-training
huggingface
TRL(Transformers Reinforcement Learning)を使用してトランスフォーマー言語モデルをトレーニングおよびファインチューニングします。SFT、DPO、GRPO、KTO、RLOO、および報酬モデルのトレーニングをサポートしています…
official
deploy-hf
huggingface
OpenEnv環境をHugging Face Spacesにデプロイします。デプロイ、Hugging Faceへのプッシュ、またはスペースの更新を求められたときに使用します。
official
hf-space-recovery
huggingface
Diagnose and recover failing or stuck Hugging Face Space deployments for OpenEnv environments. Use when deploying envs from `envs/` to the Hub (`openenv`…
official
pre-submit-pr
huggingface
プルリクエストを送信する前に変更を検証します。lint、テスト、アライメントレビュー、RFC分析を含む包括的なチェックを実行します。作成前に使用…
official
example-skill
huggingface
アクションスモークテスト用のフィクスチャスキルの例
official