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peer-review同行评审

Agent Skill

peer-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。

总安装

424

周安装

17

GitHub Stars

292

下载量

137
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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:peer-review(同行评审)
来源仓库:https://github.com/tobihagemann/turbo
仓库路径:skills/peer-review
安装命令:
npx skills add https://github.com/tobihagemann/turbo --skill peer-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/tobihagemann/turbo --skill peer-review

简介

peer-review 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、任务场景或来源线索快速定位候选结果。
  • 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,以及是否会触发联网、命令执行或文件读写。
  • 建议结合原始 README 核验具体用法和功能边界。

SKILL.md

Peer Review

Independent peer review via codex. Translates a natural-language review request into a codex-specific prompt so invocations stay implementation-agnostic.

Step 1: Understand the Request

Identify from the invoking prompt or conversation context:

  • Material — the code scope, artifact text, feedback items, or other content under review
  • Criteria — reference file paths codex should read directly, inline criteria text, or the material's own domain conventions
  • Dimensions — one review concern (single-pass) or multiple independent concerns (fan-out, one per dimension)
  • Skepticism guidance — any material-specific instruction for pushing past surface findings; optional
  • Output format — finding layout, priority scale, or verdict labels; optional

If no reviewable material is available, stop and state that material is required.

Step 2: Build the Codex Prompt

Assemble the prompt using codex's XML tag conventions (see /codex-exec Prompt Shaping):

  • <task> — the scope or material, criteria pointers (file paths codex should read, or inline criteria), and any needed context. When multiple independent dimensions are specified, wrap the dimension list with explicit parallel fan-out instructions so codex delegates each dimension to a separate spawn_agent sub-agent and waits for all before synthesizing. See /codex-exec references/parallel-execution.md for the pattern.
  • <dig_deeper_nudge> — the skepticism guidance from the request if provided; otherwise the default: "Do not stop at surface-level findings. Check for second-order failures, transformation-chain bypasses, and cases where the material relies on unstated assumptions."
  • <structured_output_contract> — the output format from the request if provided. Otherwise use the default, which aligns with the finding shape internal reviews emit so findings can be concatenated without transformation: ` ### [P<N>] <title (imperative, ≤80 chars)> **File:** <file path> (lines <start>-<end>) or **Section:** <location> **Reviewer:** peer (<dimension>) <one paragraph explaining the issue and its impact> The (lines <start>-<end>) slot is optional; include it when reviewing code, omit for section references. Include the (<dimension>)` parenthetical whenever the request identifies a dimension label (covers both single- and multi-dimension cases); omit only for undifferentiated reviews where no dimension was named. Default priority scale: P0 (fundamentally flawed or blocking), P1 (significant gap or urgent), P2 (moderate issue), P3 (minor improvement). End with an Overall Verdict block containing a 1–3 sentence assessment. If there are no issues, state that the material looks sound.

Step 3: Run /codex-exec Skill

Invoke /codex-exec via the Skill tool in read-only mode with the assembled prompt.

Step 4: Shape the Response

Compare codex's output against the dimensions and structure requested in Step 2, then classify it into one of three branches:

  • Codex returned the requested findings — output them verbatim.
  • Incomplete output (any reason — partial fan-out with missing dimensions, mid-run truncation, sections cut off, sub-agent failure, single-dimension review that ends mid-finding, etc.) — output what came back verbatim, name what is missing relative to Step 2's request, then append: "Action required: Peer review returned partial output. Use the AskUserQuestion tool to ask the user whether to retry peer review now (transient codex errors like usage limits often clear within minutes) or proceed with the partial findings. State what is missing so the user can decide."
  • No output / codex failed — output a single notice stating the cause (usage limit, error, empty response), then append: "Action required: Peer review failed. Use the AskUserQuestion tool to ask the user whether to retry peer review now (transient codex errors like usage limits often clear within minutes) or proceed without peer review."

Do not synthesize peer findings locally to fill a gap. Peer review's value is independence; locally written findings labeled "peer" mislead the consumer.

Then use the TaskList tool and proceed to any remaining task.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

37.15%
按下载量换算51

Claude

31.83%
按下载量换算44

Cursor

19.86%
按下载量换算27

Gemini CLI

8.39%
按下载量换算11

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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