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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 官方收录技能 质量 优秀 · 90 v1.0.0

获取

https://deepseekmodel.com/api/download.php?id=significant-gravitas-autogpt-claude-skills-pr-review-skill-md&format=skill
下载 .skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用
.skill 文件中 system_prompt 字段的实际内容。
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>
Agent 识别该技能的关键词,点击任意一个即可复制。

该技能未提供触发词。

下载的 .skill 包内含以下字段。
字段 说明
format格式标识(skill/v1)
skill_id技能唯一 ID
name技能名称
version版本号
description技能描述
category所属分类(数组)
trigger_words触发词列表
tags标签列表
source来源标识
source_url来源链接(本页地址)
exported_at导出时间(每次下载生成)
system_prompt系统提示词正文
model_config模型参数:provider / model / temperature / max_tokens / top_p
examples示例
install_guide各平台导入说明(Coze / Dify / Claude / 自定义框架)
同一份技能可按不同平台格式导出。
.skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用 下载
.skillpro 增强格式,额外含脚本 / 工具 / 依赖 / 钩子占位 下载
.json 纯 JSON 导出,只含 system_prompt 与模型参数 下载
Coze 带 frontmatter 的 Markdown,Coze 平台导入用 下载
Dify Dify DSL,创建应用后直接导入 下载

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