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Agent Skill · 研究检索

review-local(评论本地)

review-local 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-local 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,权限为执行命令;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 68,015。

总安装 238周安装 10GitHub Stars 10下载 83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-local(评论本地)
来源仓库:https://github.com/inkeep/team-skills
仓库路径:skills/review-local
安装命令:
npx skills add https://github.com/inkeep/team-skills --skill review-local
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/inkeep/team-skills --skill review-local

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-local 用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词快速定位结果。通过 npx skills add 命令从指定 GitHub 仓库安装使用。安装前需确认权限范围、维护状态及是否触发联网或文件操作。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/review-local

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/inkeep/team-skills --skill review-local;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

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

review-local 怎么安装?

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

review-local 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-local 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/inkeep/team-skills --skill review-local 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

review-local 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-local 用的人多吗?

公开数据是累计安装 238 次,近一周安装 10 次,下载 83 次,GitHub 10 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-local 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。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 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。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 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-local

评论本地 · 本页

23810执行命令未明确通过

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

Local Review

Run the local AI review convergence loop on the current branch. This skill dispatches domain-specific reviewers against your code, produces a structured review summary, and runs a bounded fix convergence loop — all without GitHub or a PR.

Use this as a quality checkpoint anytime you have code on a feature branch: before pushing, mid-development, or as a standalone review outside /ship.


How to invoke

Do not over-prepare. When the user asks you to run /review-local, run the script. Do not create branches, stage files, or commit on behalf of the user — the script works on the current branch state (committed + staged + unstaged).

The script path is relative to the /ship skill directory (this skill shares scripts with /ship): plugins/eng/skills/ship/scripts/run-local-review.sh

Always run with run_in_background: true — the review dispatches 17 parallel reviewers and runs fix passes, routinely exceeding the 600-second Bash timeout:

Bash(command: "<absolute-path-to-skill>/scripts/run-local-review.sh [options]",
     run_in_background: true,
     description: "Local review")

Use the absolute script path. Do not rely on CWD being correct — your shell CWD may differ from the target repo. The script resolves the repo root via git rev-parse --show-toplevel from the CWD where it is invoked, so if your CWD is a different repo, the review will run against the wrong codebase. Always invoke with the full absolute path and ensure you are in the correct repo directory.


What it runs

The script:

  1. Stages the portable PR review bundle into tmp/ship/pr-review-plugin/
  2. Dispatches 17 parallel domain-specific reviewers (via the Agent tool in their own sessions)
  3. Aggregates findings into a structured review summary
  4. Runs a bounded fix convergence loop when findings are blocking

Options

OptionDefaultDescription
--target <branch>Auto-detect (repo default branch)Branch to diff against
--max-fix-passes <n>5Maximum autonomous repair passes
--docker [compose-file]Host executionRun inside the repo's Docker sandbox
--spec <path>From state.json if existsSPEC.md path to include in repair prompts
--allow-blockingExit non-zero on blockingAccept a blocking result — exit 2 with reason allow_blocking instead of entering repair loop

Output files

All output goes to tmp/ship/:

FileDescription
review-output.mdLatest review summary (markdown)
review-status.jsonParsed status — recommendation, risk, issue counts, blocking flag, deferredFindings[]
review-iteration-log.mdFull review/fix history across iterations
local-review-runs/<run-id>/Forensic trail per review pass

Standalone usage (no /ship, no state.json)

The script works without any /ship artifacts:

  • Creates tmp/ship/ if missing
  • Detects quality gates from package.json when no state.json exists (looks for test, typecheck, lint scripts)
  • Gracefully handles missing /ship-specific files (spec.json, progress.txt, codebase-context.md — all produce _Not available._ in prompts)
  • Assessment protocol still loads from the staged review bundle

Examples

# Default: review + auto-fix loop (up to 5 passes)
<ship-skill-base>/scripts/run-local-review.sh

# Review against a specific branch
<ship-skill-base>/scripts/run-local-review.sh --target develop

# Review + fix loop (up to 2 passes)
<ship-skill-base>/scripts/run-local-review.sh --max-fix-passes 2

# Run inside Docker sandbox
<ship-skill-base>/scripts/run-local-review.sh --docker

Interpreting results

The script emits a structured return payload to stdout at exit with three delimited sections:

  1. Exit envelope (=== LOCAL REVIEW EXIT ===): Always present. Contains exit_code, exit_reason, pass counts, fix commit SHAs, last_recommendation, blocking status, duration, and file pointers.
  2. Review status (=== REVIEW STATUS ===): Parsed review-status.json content — recommendation, risk, issue counts, blocking reasons. Present on all non-crash exits.
  3. Iteration log (=== REVIEW ITERATION LOG ===): Full history of review passes and fix responses. Only included on non-zero exits (blocking/fatal) to provide remediation context.

Exit reasons:

exit_reasonExit codeMeaning
converged0Pure APPROVE — gate is green
fixer_no_changes2Fixer declined/deferred all findings, no code changed — re-reviewing would be identical
max_passes_exhausted2Still blocking after all fix passes
allow_blocking2Blocking, but --allow-blocking was set
fatal_error1Script crashed (staging, review, or parse failure)

You can also check review-status.json directly for the gate status:

  • APPROVE: Review passed — gate is green, script exits 0.
  • APPROVE WITH SUGGESTIONS: Suggestions remain. The script treats this as not-yet-converged and will attempt fix passes. Only pure APPROVE exits green.
  • REQUEST_CHANGES with Critical/Major findings: Review is blocking.

Do not blindly apply every suggestion. Validate each finding against the diff, codebase patterns, and your intent before acting.

If you are assessing review findings yourself (e.g., the automated fix loop exited non-zero and you are triaging the remaining findings manually), use the Skill tool to invoke /assess-findings before assessing any finding. Do not evaluate findings without it.

Persisting declined findings

After assessment completes (whether by the automated fix loop or manual triage), append a deferredFindings array to review-status.json containing findings from the /assess-findings Declined Findings Summary (Phase 7) where Future-relevant: Yes. Each entry:

{
  "finding": "writeTracker coupling across modules",
  "classification": "Pre-existing, out of scope",
  "evidence": "Valid encapsulation concern, not caused by this PR"
}

If no future-relevant declined findings exist, set "deferredFindings": []. This array is consumed by /ship, which persists items to state.json's deferredScope[] and surfaces them in the Ship Summary.


Relationship to /ship

/ship invokes the same run-local-review.sh script directly in Phase 4: Review gate — pre-QA (/review-local) and Phase 6: Review gate — post-QA (/review-local). /ship does not load this skill — it calls the script as an orchestrator. This skill exists for standalone human invocation outside /ship.

ContextHow invoked
Standalone (developer runs /review-local)This skill — tells the LLM what to run and where to find results
Within /ship (Phase 4 /review-local, Phase 6 /review-local)Script invoked directly by /ship orchestrator

平台分布

Codex

39.18%
按下载量换算33

Claude

27.68%
按下载量换算23

Cursor

20.34%
按下载量换算17

Gemini CLI

8.6%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/inkeep/team-skills --skill review-local 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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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