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code-review代码审查

Agent Skill

code-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

504

周安装

21

GitHub Stars

公开资料未说明

下载量

168
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:code-review(代码审查)
来源仓库:https://github.com/ankitgoyalio/everything-ai
仓库路径:skills/code-review
安装命令:
npx skills add https://github.com/ankitgoyalio/everything-ai --skill code-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/ankitgoyalio/everything-ai --skill code-review

简介

用于查找、检索和筛选相关信息,适合根据关键词快速定位候选结果。

  • 可结合来源仓库、安装命令和原始 README 继续核验具体用法。
  • 使用时需要确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。
  • 安装前建议确认权限范围和维护状态,以及是否会触发文件读写操作。
  • 适用于 Codex、Claude、Cursor、Gemini CLI 中的信息检索任务。

SKILL.md

Code Review

Run CodeRabbit through the bundled script so the workflow stays deterministic.

Use CodeRabbit as the only review source for findings. Do not add manual findings, speculative risks, or diff-based conclusions of your own.

Available Script

  • scripts/coderabbit_review.py

- review: preflight checks, scope selection, optional base resolution, CodeRabbit plain-text execution, artifact generation - render: convert the normalized JSON artifact into the required Markdown report

Resolve that path from the skill directory, not from the repository being reviewed.

Do not assume the target repository contains scripts/coderabbit_review.py.

review writes these artifacts into --output-dir:

  • progress.json: current wrapper state for polling long-running reviews
  • normalized.json: normalized wrapper artifact with metadata and captured CodeRabbit output
  • report.md: rendered Markdown report when available
  • coderabbit.stdout.log: raw CodeRabbit stdout stream
  • coderabbit.stderr.log: raw CodeRabbit stderr stream

Run python3 <skill-dir>/scripts/coderabbit_review.py --help or python3 <skill-dir>/scripts/coderabbit_review.py review --help if you need the exact interface.

Required Workflow

  1. Create a temporary artifact directory.
  2. Run the deterministic review script against the repository the user wants reviewed.
  3. If the review is long-running or launched in the background, poll progress.json in the artifact directory instead of rerunning the command.
  4. If progress.json reaches state: "artifacts_ready" or review returns status: "ok", run render on the normalized artifact.
  5. If progress.json reaches state: "error" or state: "timed_out", report the wrapper failure and include the artifact paths it produced.
  6. Return the rendered Markdown to the user when available.

Reference flow:

ARTIFACT_DIR="$(mktemp -d)"
python3 <skill-dir>/scripts/coderabbit_review.py review \
  --repo "$PWD" \
  --output-dir "$ARTIFACT_DIR"
python3 <skill-dir>/scripts/coderabbit_review.py render \
  --input "$ARTIFACT_DIR/normalized.json"

When polling:

  • prefer progress.json over terminal-session liveness
  • do not start a second review if the first run's progress.json is still updating
  • treat state: "artifacts_ready" as the success signal for rendering
  • if state: "running", the task is still in progress and you must keep polling the same artifact directory
  • while state: "running", do not return a status-only final answer and do not summarize intermediate wrapper state unless the user explicitly asks for progress
  • only stop polling when the state becomes artifacts_ready, error, or timed_out

Scope Rules

Prefer explicit scope from the user:

  • review local WIP or unstaged work: --scope uncommitted
  • review committed branch changes: --scope committed
  • otherwise let the script choose with --scope auto

Use --base <branch> only when branch comparison matters or the user explicitly names a base branch.

Only pass --config <path> when the user explicitly names additional instruction files that exist. Do not scan the repository and invent config arguments for auto-detected guideline files.

Preconditions

The script already enforces the required checks:

  • inside a Git repository
  • HEAD resolves
  • coderabbit exists on PATH
  • coderabbit auth status --agent succeeds

If preflight fails, stop and report the script's error. Do not run manual fallback review logic.

Output Contract

Return the rendered Markdown report produced by render.

The report contains:

  • summary metadata
  • the captured CodeRabbit plain-text review when available
  • structured finding sections only if CodeRabbit emits machine-readable findings despite the plain-text request

If the normalized report contains zero structured findings but includes plain-text review output, return that result directly. Do not add extra concerns.

Source Policy

  • Use only CodeRabbit output for findings.
  • Do not inspect the diff to add new findings.
  • Do not override or suppress findings unless they are exact duplicates merged by the script.
  • Keep any explanation faithful to the normalized CodeRabbit output.

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

35.53%
按下载量换算60

Claude

30.31%
按下载量换算51

Cursor

20.82%
按下载量换算35

Gemini CLI

10.31%
按下载量换算17

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/ankitgoyalio/everything-ai --skill code-review 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。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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