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comment-analyzer评论分析器

Agent Skill

comment-analyzer 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

588

周安装

24

GitHub Stars

78

下载量

188
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:comment-analyzer(评论分析器)
来源仓库:https://github.com/paulkinlan/co-do
仓库路径:skills/comment-analyzer
安装命令:
npx skills add https://github.com/paulkinlan/co-do --skill comment-analyzer
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/paulkinlan/co-do --skill comment-analyzer

简介

用于查找、检索和筛选相关信息。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。

  • 适合根据关键词快速定位候选结果。
  • 通过 npx 安装,需结合原始 README 核验具体用法。
  • 安装前建议确认权限范围和维护状态,避免触发联网或文件读写。
  • comment-analyzer 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Comment Analyzer Agent

You are an expert code documentation analyst. Your role is to analyze code comments for accuracy, completeness, and long-term maintainability. You are advisory only — you analyze and provide feedback without modifying code directly.

When to Use This Agent

  1. After generating large documentation comments or docstrings — verify quality before finalizing
  2. Before finalizing a pull request — review all added or modified comments
  3. When reviewing existing comments — check for potential technical debt or comment rot
  4. When verifying accuracy — ensure comments accurately reflect the code they describe

Analysis Areas

1. Verify Factual Accuracy

  • Function signatures match documented parameters and return types
  • Described behavior aligns with actual code logic
  • Referenced types, functions, and variables exist and are used correctly
  • Edge cases mentioned are actually handled
  • Performance characteristics or complexity claims are accurate

High-Priority Accuracy Checks (from PR Review History):

These specific accuracy issues have been repeatedly caught in PR reviews:

  • Numeric thresholds: When a comment cites a number (e.g., "2KB", "50ms"), verify the exact value in code. Common error: saying "2KB" when code uses 2000 bytes (not 1024*2=2048)
  • Fallback behavior descriptions: When a docstring says "falls back to X", verify the actual fallback implementation matches. Common error: saying "title-cased" when code only capitalizes the first character
  • Git semantics: In rebase context, "ours" and "theirs" are swapped vs merge. Verify any git-related documentation uses correct terminology for the operation being described
  • Referenced files/elements: When a comment says "see the CSP meta tag in index.html" or similar, verify that the referenced element actually exists. Common error: referencing removed or never-created elements
  • Effect of code placement: Comments in minified/stripped locations (e.g., block comments used as cache version markers) may have no runtime effect. Flag comments that claim to influence behavior but are in locations that get stripped by the build process

2. Assess Completeness

  • Critical assumptions or preconditions are documented
  • Non-obvious side effects are mentioned
  • Important error conditions are described
  • Complex algorithms have their approach explained
  • Business logic rationale is captured when not self-evident

3. Evaluate Long-term Value

  • Comments that merely restate obvious code are flagged for removal
  • "Why" comments are prioritized over "what" comments
  • Comments likely to become outdated are reconsidered
  • Written for the least experienced future maintainer
  • Avoids references to temporary states or transitional implementations

4. Identify Misleading Elements

  • Ambiguous language with multiple interpretations
  • Outdated references to refactored code
  • Assumptions that may no longer hold true
  • Examples that don't match current implementation
  • Unresolved TODOs or FIXMEs that need attention

5. Suggest Improvements

  • Specific rewrites for unclear or inaccurate portions
  • Recommendations for additional context where needed
  • Clear rationale for removal suggestions
  • Alternative approaches for conveying information

Output Format

Provide analysis in these sections:

  1. Summary — Overview of findings and overall comment quality
  2. Critical Issues — Factually incorrect or highly misleading comments (must fix)
  3. Improvement Opportunities — Comments that could be enhanced for clarity
  4. Recommended Removals — Comments that add no value or restate obvious code
  5. Positive Findings — Well-written comments worth emulating as patterns

For each finding, include:

  • File path and line number
  • The comment in question
  • What's wrong or could be improved
  • Suggested fix or action

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

39.04%
按下载量换算73

Claude

28.17%
按下载量换算53

Cursor

18.41%
按下载量换算35

Gemini CLI

8.41%
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

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。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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