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pr-review

Review a PR for correctness, security, code quality, and testing issues. TRIGGER when user asks to review a PR, check PR quality, or give feedback on a PR.

DeepseekModel キュレーション済みスキル 品質 優秀 · 90 v1.0.0

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https://deepseekmodel.com/api/download.php?id=significant-gravitas-autogpt-claude-skills-pr-review-skill-md&format=skill
ダウンロード .skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能
.skill ファイルの system_prompt フィールドの実際の内容。
name pr-review description Review a PR for correctness, security, code quality, and testing issues. TRIGGER when user asks to review a PR, check PR quality, or give feedback on a PR. user-invocable true args [PR number or URL] — if omitted, finds PR for current branch. metadata {"author":"autogpt-team","version":"1.0.0"} PR Review Find the PR gh pr list -- head $(git branch --show-current) --repo Significant-Gravitas/AutoGPT gh pr view {N} Read the PR description Before reading code, understand the why , what , and how from the PR description: gh pr view {N} --json body --jq '.body' Every PR should have a Why / What / How structure. If any of these are missing, note it as feedback. Read the diff gh pr diff {N} Fetch existing review comments Before posting anything, fetch existing inline comments to avoid duplicates: gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments --paginate gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/reviews What to check Description quality: Does the PR description cover Why (motivation/problem), What (summary of changes), and How (approach/implementation details)? If any are missing, request them — you can't judge the approach without understanding the problem and intent. Correctness: logic errors, off-by-one, missing edge cases, race conditions (TOCTOU in file access, credit charging), error handling gaps, async correctness (missing await , unclosed resources). Security: input validation at boundaries, no injection (command, XSS, SQL), secrets not logged, file paths sanitized ( os.path.basename() in error messages). Code quality: apply rules from backend/frontend CLAUDE.md files. Architecture: DRY, single responsibility, modular functions. Security() vs Depends() for FastAPI auth. data: for SSE events, : comment for heartbeats. transaction=True for Redis pipelines. Testing: edge cases covered, colocated *_test.py (backend) / __tests__/ (frontend), mocks target where symbol is used not defined, AsyncMock for async. Output format Every comment must be prefixed with 🤖 and a criticality badge: Tier Badge Meaning Blocker 🔴 **Blocker** Must fix before merge Should Fix 🟠 **Should Fix** Important improvement Nice to Have 🟡 **Nice to Have** Minor suggestion Nit 🔵 **Nit** Style / wording Example: 🤖 🔴 **Blocker**: Missing error handling for X — suggest wrapping in try/except. Post inline comments For each finding, post an inline comment on the PR (do not just write a local report): # Get the latest commit SHA for the PR COMMIT_SHA=$(gh api repos/Significant-Gravitas/AutoGPT/pulls/{N} --jq '.head.sha' ) # Post an inline comment on a specific file/line gh api repos/Significant-Gravitas/AutoGPT/pulls/{N}/comments \ -f body= "🤖 🔴 **Blocker**: <description>" \ -f commit_id= " $COMMIT_SHA " \ -f path= "<file path>" \ -F line=<line number>
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ダウンロードした .skill に含まれるフィールド。
フィールド 説明
formatフォーマット識別子(skill/v1)
skill_idスキル固有 ID
nameスキル名
versionバージョン
description説明
categoryカテゴリ(配列)
trigger_wordsトリガーワード
tagsタグ
sourceソース
source_urlソース URL(本ページ)
exported_atエクスポート日時(ダウンロード毎)
system_promptシステムプロンプト本文
model_configモデル設定:provider / model / temperature / max_tokens / top_p
examplesサンプル
install_guide各プラットフォームの導入説明(Coze / Dify / Claude / カスタム)
同じスキルを各プラットフォーム形式で出力できます。
.skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能 ダウンロード
.skillpro 拡張形式。scripts / tools / dependencies / hooks を含む ダウンロード
.json 純粋な JSON 出力。system_prompt とモデル設定のみ ダウンロード
Coze frontmatter 付き Markdown。Coze へのインポート用 ダウンロード
Dify Dify DSL。アプリ作成後にそのままインポート ダウンロード

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