ai-assist-git-pr-review

审查 · 54
已收录

Perform a standards-based code review on a GitHub Pull Request, then post the findings as inline review comments and mark the PR as 'Requested changes'. Reads all of the agents files that exist in the repository under review (AGENTS.md, .agents-docs/, CLAUDE.md on the PR's base b

Verified installs0
Stars88
版本1.0.0
质量61/100 · 有潜力
信任54/100 · Do not auto-install
审计70/100 · 需审查

供给资产档案

编程与开发 Agent

代码审查、仓库分析、测试、CI、GitHub、DevOps 与开发工作流 Skill。

浏览赛道

场景

GitHub automation

I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.

适配 Agent

Claude Code + CLI + Codex

适用于 Codex、Claude Code、Cursor、CLI 或自定义 Agent。

安装

就绪

npx skills add jparkerweb/ai-assist-skills --skill ai-assist-git-pr-review

维护状态

新鲜

今天有推送

风险

需审查

许可证不清晰

GitHub 质量

88

61/100 质量 · 62/100 信任

覆盖标签

编程GitHub automation编程 Agentagent-skill

审查说明

许可证不清晰 · Dependency or permission surface needs review

Agent 采用评分卡

一眼查看信任、审计与安装准备度

这些分数综合公开仓库元数据、OpenAgentSkill 审查信号、维护新鲜度与安装准备度。它用于候选筛选,不替代人工审查。

质量

有潜力
61

有用的候选项,但采用前应与替代方案比较。

信任

Do not auto-install
54

Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.

审计

需审查
70

对安装准备度、安全元数据、维护情况与采用风险的机器可读审查。

OpenAgentSkill 信任评分 v5

安装前需人工审查

Choose a stronger alternative or inspect the source manually before any install attempt.

CodexClaude CodeCursorOpenAgentSkill CLI

Stars

88 个 GitHub Stars

仓库活跃度

88 个 Star,12 个 Fork

维护状态

今天有推送

许可证

未知

安装

npx skills add jparkerweb/ai-assist-skills --skill ai-assist-git-pr-review

安装安全性

标准软件包或运行时安装路径

权限范围

secrets or environment access, shell or command execution

Agent 结果

暂未有 Agent 结果数据

文档

README/SKILL.md 上下文充分

风险摘要

生产前审查

  • Repository license is unknown; clarify licensing for the skill.
  • 许可证不清晰
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution

安装准备度

安装路径可用

  • 安装路径可用
  • 仓库证据可用
  • 许可证不清晰
  • 暂无 Agent 验证结果证据

Agent 可读元数据

这个 Skill 的机器可读决策数据。

使用此区块或内嵌 JSON 判断 Agent 是否应安装该 Skill、选择替代方案,或先请求人工审查。

打开 JSON

适用任务

  • GitHub automation 工作流
  • Claude Code 团队
  • builders willing to evaluate younger projects
  • Inspect repository metadata

适用 Agent

CodexClaude CodeCursorOpenAgentSkill CLICLI

安装决策

命令
npx skills add jparkerweb/ai-assist-skills --skill ai-assist-git-pr-review
策略
阻止
人工审查

信任与风险

信任
54/100
审计
70/100
风险级别
需审查

结果闭环

端点
/api/agent/outcome
事件 ID
resolve
结果
5

安装命令

npx skills add jparkerweb/ai-assist-skills --skill ai-assist-git-pr-review

不适用场景

  • 需要厂商支持 SLA 的团队
  • production agents without a repository review
  • Repository license is unknown; clarify licensing for the skill.
  • 高风险权限提示:Shell or command execution, Secrets or environment access
  • 许可证不清晰

Agent 安全 v2

22/100 · 避免自动安装

Blocked for auto-install阻止

This skill should not be selected by an agent without explicit human security review.

Do not auto-install. Inspect the source, dependencies, and permission surface first.

通过 API 解析

Shell 或命令执行

Skill 元数据引用了终端、CLI、Shell、子进程或命令执行工作流。

Browser automation

Skill may drive a browser or interact with web pages.

网络访问

Skill 可能访问远程页面、API、仓库或外部服务。

文件系统访问

Skill 可能读取或写入项目文件、文档、生成产物或本地工作区状态。

  • 高风险权限提示:Shell or command execution, Secrets or environment access
  • 许可证不清晰

安装目标

在你的 Agent 工作流中安装此 Skill

通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。

skill install

OpenAgentSkill CLI

Resolve policy, run the source installer safely, and report a verified install receipt.

$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install jparkerweb-ai-assist-git-pr-review

Agent 解析计划

让 Agent 在安装前验证匹配度。

Resolve API 返回首选 Skill、替代方案、安全策略、审计说明、安装目标和可直接执行的提示词,无需抓取此页面。

打开文本计划

Agent 应检查

  • 从 Resolve API 检查任务匹配与替代方案。
  • 检查审计评分、信任评分和安全策略警告。
  • 检查 Codex、Claude Code、Cursor 或 CLI 的安装目标兼容性。

复制提示词

Task: Use ai-assist-git-pr-review in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20ai-assist-git-pr-review%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/jparkerweb-ai-assist-git-pr-review/install
Install command: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-git-pr-review
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.

Agent 交接

把安装路径交给 Agent,而不是再给一个目录页。

通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。

打开安装 API

Agent 提示词

Use ai-assist-git-pr-review for this task. Review https://www.openagentskill.com/api/skills/jparkerweb-ai-assist-git-pr-review/install, then install with: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-git-pr-review

Registry 元数据

用于自动选择 Skill 的 Agent 可读档案。

本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号,让 Agent 无需抓取界面即可排序。

打开 Manifest

适配 Agent

61/100

GitHub automation

平台

Claude Code

审计报告

需审查 · 70/100

对安装准备度、安全元数据、维护情况与采用风险的机器可读审查。

查看审计报告查看评估报告

Agent 决策面板

Fallback candidate for GitHub automation

先用此 Skill 做原型验证,并保留备选方案。

61
就绪度
原型验证
阶段

栈中角色

备选候选

主要匹配

GitHub automation

信任标签

先做原型验证

安装路径

命令已就绪

适用场景

  • GitHub automation 工作流
  • Claude Code 团队
  • builders willing to evaluate younger projects

证据

  • 仓库近期活跃
  • 已提供安装命令或 GitHub 仓库
  • 61/100 质量档案
  • 3 个 OpenAgentSkill 交互事件

先审查

  • Repository license is unknown; clarify licensing for the skill.

实施路径

  1. 1在沙盒 Agent 中安装它,并端到端完成一次GitHub automation任务。
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.

信任档案

Do not auto-install

Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.

54
OpenAgentSkill 信任评分

GitHub 采用度

检查

88 个 GitHub Stars

Star/Fork 活跃度

检查

88 个 Star,12 个 Fork; 当前元数据中没有议题活跃度信息

近期维护

通过

今天有推送

许可证清晰度

检查

未知

积极信号

  • AI 审查已通过
  • 安装路径可用
  • 仓库证据可用
  • 近期维护的仓库
  • 安装命令未发现明显高风险模式
  • 结果闭环已就绪,但需要首次真实 Agent 运行

安装前审查

  • Repository license is unknown; clarify licensing for the skill.
  • 许可证不清晰
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • GitHub adoption: 88 GitHub stars
  • Stars/forks activity: 88 stars, 12 forks; issue activity unavailable in current metadata
  • License clarity: Unknown
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution
  • 暂未有真实 Agent 结果报告
  • 无人值守安装前需要人工审查

建议操作

Choose a stronger alternative or inspect the source manually before any install attempt.

质量档案

有潜力 适用于 Agent 工作流的候选

有用的候选项,但采用前应与替代方案比较。

61
GitHub Stars
88
新鲜度
今天
安装就绪
许可证
未知
安装前审查: Repository license is unknown; clarify licensing for the skill.

工作流匹配

在这些场景使用此 Skill

工作流匹配

加入完整工作流

替代方案短名单

安装前对比

可能适合该任务的相近 Skill。

对比全部

概览

--- name: ai-assist-git-pr-review description: "Perform a standards-based code review on a GitHub Pull Request, then post the findings as inline review comments and mark the PR as 'Requested changes'. Reads all of the agents files that exist in the repository under review (AGENTS.md, .agents-docs/, CLAUDE.md on the PR's base branch) — the repo's full documented standards, not just any agents files the PR happens to change — checks the diff against them plus general best practices, and gates every write behind explicit approval. Use this skill whenever the user wants to code-review a PR, review a pull request, check a PR against standards, request changes on a PR, or gives you a GitHub PR link and asks for a review. Also triggers on: 'review this PR', 'code review', 'review PR', 'check this pull request', 'request changes', 'review against our standards', or a bare github.com/.../pull/<n> URL with review intent. This is a review-only skill — it never approves, merges, closes, or pushes code." argument-hint: "[PR URL] — e.g. 'https://github.com/org/repo/pull/42' or 'review https://github.com/org/repo/pull/42'" ---

# PR REVIEW

**Objective:** Review a GitHub PR against documented standards (its agents files) plus general engineering best practices, then — after your explicit approval — post the findings as inline review comments and submit the review as **REQUEST_CHANGES**.

**Role:** Senior reviewer writing for senior engineers. Read the diff deeply, ground every finding in evidence (a cited standard or a concrete code risk), and keep comments short and actionable. A good review reads like it came from a careful teammate, not a linter.

Start each response with `🔍 [PR Review — Step X: Name]` so the user can follow the flow.

## Safety Model

| Level | Actions | Behavior | |-------|---------|----------| | **Auto** | Read PR metadata, diff, changed files, agents files, existing review threads; analyze and de-duplicate | Execute immediately | | **Gated** | Post the review (inline comments + REQUEST_CHANGES) | Preview every comment → explicit approval → post → verify | | **Blocked** | Approve, merge, close, push, edit code, dismiss reviews | Never. This skill only *requests changes*. |

The single write in this skill is posting the review. Nothing reaches GitHub until the user has seen every comment and approved. This matters because a review is visible to the whole team and notifies the author — surprising them with unreviewed machine output erodes trust in the tool.

## Prerequisites

**gh CLI (BLOCKING — before any `gh` command):** run `gh --version` first. If it fails, the CLI isn't installed — tell the user to install and authenticate GitHub CLI (`gh auth login`), then stop. If `gh auth status` fails, prompt them to authenticate. Don't attempt other `gh` calls until both pass.

## Process

### Step 1: Get the PR link

The PR URL may be in `$ARGUMENTS`. If it isn't, ask: *"Which PR would you like me to review? Paste the GitHub PR link."* Don't guess or assume the current branch — this skill reviews an arbitrary PR by URL, which may live in a different repo than the current directory.

Parse the URL `https://github.com/<owner>/<repo>/pull/<number>` into `$owner`, `$repo`, `$number`. If it doesn't match that shape, ask the user to re-paste a full PR URL.

### Step 2: Load PR context

Fetch metadata (single call):

```bash gh api repos/$owner/$repo/pulls/$number \ --jq '{title, state, draft, headSha: .head.sha, baseRef: .base.ref, changedFiles: .changed_files, additions, deletions, author: .user.login}' ```

- **state != "open"** → stop: "PR #N is <state>. Reviews can only be posted on open PRs." (A closed/merged PR can't receive a REQUEST_CHANGES review.) - Capture `headSha` — you'll pin the review to it so comments land on the exact revision you reviewed. - If it's a draft, note it but continue (drafts can still be reviewed).

### Step 3: Gather the standards (the agents files)

The whole point of this review is conformance to *this repo's* documented standards, so read them from the PR's repo — not the local workspace, which may be a different project. **These are the agents files that exist in the repository, which define the standards — not merely the agents files the PR happens to modify.** A PR usually doesn't touch the agents docs at all; you still read the repo's full set to know the rules the changed code must follow. See `references/posting-review.md` §Gathering Agents Files for the exact `gh api` calls. In short:

1. List the **entire** repo tree on the PR's base branch and find every agents file present in the repo: `AGENTS.md`, `CLAUDE.md`, anything under `.agents-docs/`, and any `AGENTS.md`/`CLAUDE.md` in subdirectories. Do this against the full tree, independent of what the PR changed. 2. Read them. `AGENTS.md` files are usually a lightweight index that links to detailed docs under `.agents-docs/` — follow the links for any area the diff touches (e.g. if the PR changes C# code, read the C# coding-standards doc). 3. Distill a working checklist of concrete, checkable rules (commit format, naming, layering/wrapper boundaries, test structure, forbidden patterns, etc.). Keep the rules and *where each came from* so every finding can cite its source.

If the repo has **no** agents files, tell the user and offer to proceed on general best practices alone — the review is weaker without documented standards, so let them decide.

### Step 4: Fetch the diff and review

Get the changed files and the diff:

```bash gh pr diff $number --repo $owner/$repo ```

For any changed file where you need full surrounding context (not just the hunk), read it from the PR head: see `references/posting-review.md` §Reading a File at the PR Head. Don't review from hunks alone when a rule depends on context the hunk doesn't show (e.g. "private methods below public methods" needs the whole class).

**Evaluate each change against, in priority order:** 1. **Documented standards** from Step 3 — the primary bar. A violation of a written team rule is always worth flagging. 2. **General best practices** — obvious bugs, security issues (injection, secrets, auth gaps), missing null/error handling, race conditions, performance cliffs, and clear maintainability problems, even when no agents file mentions them.

**What NOT to flag (this matters — over-flagging erodes trust in the review):** - **Style the docs only *illustrate*, not *mandate*.** A code sample in an agents doc shows one way to write something; it is not a rule. Bracket-quoting object names, `BEGIN/END` wrappers, brace placement, and similar formatting choices are not findings unless a doc states them as an explicit requirement ("must", "always", a rule in prose — not just an example snippet). When in doubt, treat it as illustrative and stay silent. - **Personal-preference refactors** with no functional or documented basis. If you'd only be substituting your taste for the author's, don't comment. - **Speculative concerns** you can't ground in the diff, a cited standard, or a concrete risk. Every comment must trace to a rule or a real problem — if you can't name the basis, drop it.

A short review of real issues is worth far more than a long one padded with style opinions.

**Categorize each finding by severity** (this is what the user asked to see so they can triage NIT vs must-fix):

| Severity | Meaning | Examples | |----------|---------|----------| | **CRITICAL** | Must fix before merge — correctness, security, or data-loss risk; or a hard team rule that will break CI/deploy | SQL injection, leaked secret, null deref on a hot path, wrong commit format that the CI gate rejects, calling ServiceRepositories directly when the repo forbids it | | **WARNING** | Should fix — bug risk, missing validation/error handling, a documented convention violated, measurable perf issue | Swallowed exception, missing test for new logic, naming that violates the coding-standards doc, N+1 query | | **NIT** | Optional — style, readability, minor refactor with no functional impact | Import ordering, comment wording, a slightly cleaner idiom |

Anchor each finding to a specific `path` + `line` **that appears in the diff** (`side: RIGHT` for added/context lines, `LEFT` for deleted). This skill posts **inline comments only — no summary write-up of the PR.** A finding that doesn't map neatly to a changed line should be anchored to the nearest related changed line (e.g. attach a "missing test" note to the new file's `CREATE`/signature line); if it genuinely can't be tied to any changed line, drop it rather than writing a prose summary. See `references/posting-review.md` §Anchoring Rules.

Be disciplined about noise: don't invent findings to look thorough. If the PR is genuinely clean, it's fine to end up with only one or two comments — quality over volume.

### Step 5: De-duplicate against existing review threads

Before presenting anything, read the review activity that is **already on the PR** and classify each of your candidate findings as either **new** or **already-raised**. Other reviewers — human teammates and bots like GitHub Copilot and Devin Review — have often already raised the same points, and the author may have fixed them, replied with a rationale, or consciously declined. You must **not silently repost** an already-raised point (that relitigates a settled thread and signals you didn't read it) — but you must **not silently drop it either**. Instead, set already-raised findings aside and surface them to the user in Step 6 as items to review, so *they* decide whether the prior dismissal/resolution was actually correct. This step is mandatory, not optional. See `references/posting-review.md` §Gathering Existing Review Threads for the exact `gh api`/GraphQL calls. In short:

1. Fetch **all** prior review activity: inline review comments (`/pulls/$number/comments`), review summaries (`/pulls/$number/reviews`), and issue-level comments (`/issues/$number/comments`) — from every author, including bots (`Copilot`, `devin-ai-integration[bot]`, etc.) and the PR author's own replies. Also pull each thread's **resolved/outdated** status via GraphQL, which is a strong "already handled" signal. 2. For every candidate finding from Step 4, check whether an existing thread already covers the same issue on the same file/area. Classify it as **already-raised** if any of these hold (record *which* signal, *who* raised it, and *how* it was handled — replied/declined/resolved/outdated/fixed — you'll show this in Step 6): - A prior comment makes substantially the same point (even if worded differently or at a slightly different line). - The author (or anyone) **replied** to that thread dismissing it with a rationale or explaining it's intentional. - The thread is marked **resolved** or **outdated**, or the code it pointed at has since changed (a fix likely landed). 3. Everything else is a **new** finding. For each already-raised finding, also form a quick judgment: does the prior resolution look sound, or does it seem prematurely dismissed / not actually addressed? You'll present that assessment alongside the item so the user can decide whether to re-raise it.

Both buckets go to the user in Step 6 — **new** findings as proposed comments, **already-raised** findings as review items. Never auto-post an already-raised finding; only include it in the posted review if the user explicitly tells you to re-raise it.

### Step 6: Present findings for approval (GATED)

Show the user the complete set of inline comments before anything is posted. Use this structure:

``` 🔍 Review of PR #<n> — <title> Standards source: <which agents files informed this>

New findings — will be posted if approved (<count>): 1. [CRITICAL] <path>:<line> — <one-line finding> (cites: <standard or "best practice">) > <the exact comment body that will be posted> 2. [WARNING] <path>:<line> — ... 3. [NIT] <path>:<line> — ...

Already raised by others — NOT posted, for your review (<coun

技术详情

版本
1.0.0
许可证
Unknown
最近更新
2026年8月22日
发布时间
2026年8月21日

决策摘要

备选候选

61
就绪
原型验证
阶段

仓库近期活跃

审计

安装审查

安装与采用审查

70
需审查
安全性
63/100
维护状态
100/100
安装
92/100
打开完整审计查看评估报告

Agent 验证证据

Agent 验证证据

来自解析、审查、安装和一次小范围运行后的结果报告。

0
已验证
Needs first agent run自动安装: 先审查最近: 未知
成功率
近期失败
结果
0
输出质量
失败
0
不相关
0
安装次数
0
风险拦截
0
需要配置
0
生产环境
0

暂时没有 Agent 结果数据。首次 Agent 执行可以通过 /api/agent/outcome 报告成功、需要设置、风险拦截、失败或不相关。

安装

加入 Agent 工作流

免费且开源. 在生产 Agent 中安装前请先审查报告。

增长闭环

分享工具包

X

为 ai-assist-git-pr-review 准备的场景化草稿,可手动发布到 X。

策展说明
ai-assist-git-pr-review: Perform a standards-based code review on a GitHub Pull Request, then post the findings as inl...

88 stars

https://www.openagentskill.com/skills/jparkerweb-ai-assist-git-pr-review?ref=x
打开 X 草稿
可选:带安装命令的回复
Listing + install path for ai-assist-git-pr-review:
https://www.openagentskill.com/skills/jparkerweb-ai-assist-git-pr-review?ref=x

Install: npx skills add jparkerweb/ai-assist-skills --skill ai-assist-git-pr-review
打开回复草稿

收录来源

Registry 收录

可认领

此列表来自公开来源,维护者认领获批前不会标记为官方。

创作者
jparkerweb
收录方
OpenAgentSkill 社区索引

归属链接指向公开仓库或创作者主页。创作者可认领列表以更新所有权信号。

认领此 Skill

所有者认领

认领此 Skill 页面

这条 Registry 收录 列表归属于 jparkerweb,但尚未标记为官方。认领后可增加已验证所有者信号,使后续发布、安装和审计更新更值得信赖。

创作者外链工具包

将证据徽章加入你的 README

在开发者评估仓库的位置展示规范页面、当前信任与审计信号,以及真实的 Agent 验证证据。

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/jparkerweb-ai-assist-git-pr-review?metric=listed&label=Listed)](https://www.openagentskill.com/skills/jparkerweb-ai-assist-git-pr-review)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/jparkerweb-ai-assist-git-pr-review?metric=trust&label=Trust)](https://www.openagentskill.com/skills/jparkerweb-ai-assist-git-pr-review)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/jparkerweb-ai-assist-git-pr-review?metric=audit&label=Audit)](https://www.openagentskill.com/skills/jparkerweb-ai-assist-git-pr-review/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/jparkerweb-ai-assist-git-pr-review?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/jparkerweb-ai-assist-git-pr-review)

作者

J

jparkerweb

@jparkerweb

平台适配

健康信号

GitHub Stars
88
质量评分
36/100
最近 GitHub 推送
2026年8月22日
框架提示
未知
OpenAgentSkill 浏览量
3
复制安装命令
0
跳转点击
0

社区信号

告诉我们这个 Skill 是否对你的 Agent 工作流有帮助。汇总反馈会持续改善排序。

信任与安全

Do not auto-install

54
  • GitHub 采用度88 个 GitHub Stars检查
  • Star/Fork 活跃度88 个 Star,12 个 Fork; 当前元数据中没有议题活跃度信息检查
  • 近期维护今天有推送通过
  • 许可证清晰度未知检查
  • README/SKILL.md 完整度元数据包含足够的用法与工作流上下文通过
  • 依赖与运行时风险command execution surface, credential or environment access修复