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Agent Skill · 研究检索

review(审查)

review 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

review 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 53,604。

总安装 528周安装 22GitHub Stars 2下载 176核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:review(审查)
来源仓库:https://github.com/uinaf/skills
仓库路径:skills/review
安装命令:
npx skills add https://github.com/uinaf/skills --skill review
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/uinaf/skills --skill review

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

review 用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。可结合来源仓库和原始 README 核验具体用法。安装前建议确认权限范围和维护状态。review 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

注意是否会触发联网、命令执行或文件读写。

来源仓库内路径:skills/review

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/uinaf/skills --skill review;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

review 怎么安装?

在终端执行 npx skills add https://github.com/uinaf/skills --skill review。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

review 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

review 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

review 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

review 用的人多吗?

公开数据是累计安装 528 次,近一周安装 22 次,下载 176 次,GitHub 2 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

review 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
review

审查 · 本页

5282只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Review

Independently audit existing code with concern-specific lenses and decide whether it is safe to ship. Review is the gate after verify — the builder proves the change works on the real surface, then review decides whether the change is *good*.

Principles

  • Prefer parallel reviewer personas when the concerns are independent
  • Evidence beats taste
  • Load shared doctrine from the target repo's guidance files such as AGENTS.md, CLAUDE.md, or repo rules
  • Keep the final verdict tied to concrete evidence, not reviewer instinct alone
  • Keep findings risk-focused; do not drown the user in low-value nits
  • Track reviewer personas internally; include them visibly only when asked or when the harness has compact metadata
  • If runtime proof for your own completed change is the goal, hand off to verify

Handoffs

  • Self-checking a change you just authored, before handing it off for review → use verify
  • Review is blocked because the repo cannot be booted or exercised reliably → use agent-readiness
  • Main problem is stale AGENTS.md, README, specs, or repo docs → use docs

Before You Start

  1. Define the scope: file, diff, branch, commit range, or PR
  2. Load the target repo's guidance files such as AGENTS.md, CLAUDE.md, or repo rules, when present
  3. Choose reviewer personas from references/reviewer-selection.md
  4. Decide which personas can run independently in parallel

Default personas:

Add conditional personas only when they earn their keep:

Persona shortcuts:

  • doc-only or comment-only diffs: use general plus comments; skip tests, types, silent-failures, and cleanup unless the diff actually justifies them
  • type-shape or schema changes: add types
  • dead files, deprecated paths, or obviously unused helpers: add cleanup and call out deletion explicitly when warranted
  • mock-heavy or shallow tests around risky behavior: make that a finding rather than treating test presence as proof

Workflow

1. Scope nearby risk

Review the requested code, but inspect adjacent behavior when the risk leaks past the named diff.

2. Run reviewer personas

Use parallel subagents when available. Keep each persona concern-focused and independent.

Concrete starting points:

  • git diff --stat <base>...HEAD to size the change
  • git diff <base>...HEAD -- <path> to inspect risky files
  • targeted tests such as pnpm test path/to/spec when behavior claims need proof

3. Collect evidence

  • Cite exact file references for static findings
  • Run the smallest runtime check that changes the verdict when the repo supports it
  • If something is unverified, say so explicitly instead of bluffing
  • If legacy or dead code is still present, say whether it should be deleted or why it must stay
  • If tests mock the main integrations or boundaries, say that the behavior is still unverified on the real surface

4. Synthesize the verdict

Order findings by severity. If no findings are discovered, say that explicitly and mention any residual risk or testing gap. Choose exactly one verdict: ship it, needs review, or blocked.

Output

After review, report a tiny verdict footer:

  • verdict
  • evidence summary: exact command names or runtime surfaces, not full logs
  • unverified areas or readiness gaps
  • next: implementation, verify, agent-readiness, or docs

Use those labels explicitly. Do not replace them with softer prose like "safe to merge" or "do not ship today".

Prefer the active harness's best native review representation instead of a prose-heavy wall of text.

Keep the final answer short:

  • Put detailed issue text, file references, and line numbers in native findings or the fallback findings list
  • Do not repeat native finding details in the verdict block
  • Keep the verdict footer to 4 labeled lines or fewer
  • Keep each label to one sentence; use comma-separated command names instead of log excerpts
  • Omit scope and personas from the footer unless the user asked for them or the scope would be ambiguous without one short reviewed: line
  • If there are no findings, say findings: none and keep the rest equally compact

Harness-specific presentation rules:

  • Prefer the strongest structured finding format available: Codex/OpenAI native P0 / P1 / P2 / P3 cards, or a compact table in Claude/Anthropic harnesses
  • If no richer primitive exists, use a short severity-ordered findings list with file/line, issue, impact, and evidence
  • Never hide actionable findings inside the footer or a long prose recap

Example:

verdict: needs review
finding: high — src/auth/session.ts:42 fallback returns an anonymous session when token parsing fails
evidence: pnpm test src/auth/session.test.ts
unverified areas: runtime behavior for malformed OAuth callbacks
next: implementation

References

平台分布

Codex

31.74%
按下载量换算56

Claude

29.65%
按下载量换算52

Cursor

19.7%
按下载量换算35

Gemini CLI

8.97%
按下载量换算16

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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