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Agent Skill · 研究检索

pr-writing-review(公关写作评论)

用于辅助文档、README、Markdown、说明文和内容稿件的整理与改写。它适合让 Agent 提炼结构、补齐章节、统一术语、检查链接或把零散材料整理成可读文档。使用时应保留项目已有事实、命令和路径,不要把未确认的信息写成确定结论;涉及对外文案时,还需要控制语气,避免过度营销或夸大能力。

pr-writing-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,权限为调用外部服务;许可证信息还不明确,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 50,054。

总安装 630周安装 26GitHub Stars 3,676下载 206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:pr-writing-review(公关写作评论)
来源仓库:https://github.com/evalstate/fast-agent
仓库路径:skills/pr-writing-review
安装命令:
npx skills add https://github.com/evalstate/fast-agent --skill pr-writing-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/evalstate/fast-agent --skill pr-writing-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。

pr-writing-review 用于辅助文档、README、Markdown、说明文和内容稿件的整理与改写。适用于检查文案逻辑、术语一致性与可读性,提升对外沟通质量。支持识别冗余表达、修正语法错误并提供优化建议。使用时需保留项目原有事实与路径信息,避免虚构未确认的数据。

涉及对外发布内容时,应控制语气避免过度营销或夸大能力。

来源仓库内路径:skills/pr-writing-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/evalstate/fast-agent --skill pr-writing-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

    它需要调用外部服务,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

pr-writing-review 怎么安装?

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

pr-writing-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。

pr-writing-review 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

pr-writing-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。

pr-writing-review 用的人多吗?

公开数据是累计安装 630 次,近一周安装 26 次,下载 206 次,GitHub 3,676 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。

pr-writing-review 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

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。
  • 来源仓库有 3,676 星,维护活跃度相对可查。

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。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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

  • 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
pr-writing-review

公关写作评论 · 本页

6303,676调用外部服务未明确未通过

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

PR Writing Review

Extract editorial feedback from GitHub PRs to learn from review improvements.

Prerequisites

  • GitHub CLI: gh installed
  • Authenticated gh session: gh auth status should show you’re logged in

- For private repos, your token needs appropriate scopes (typically repo).

Division of Labor

ToolResponsibility
Python scriptAPI calls, parsing, file tracking across renames, structured extraction
LLM analysisPattern recognition, paragraph comparison, style lesson synthesis

Quick Start

> **All paths are relative to the directory containing this SKILL.md file.**
> Before running any script, first `cd` to that directory or use the full path.

# Get suggestions and feedback
uv run scripts/extract_pr_reviews.py <pr_url>

# Get full first→final comparison for deep analysis
uv run scripts/extract_pr_reviews.py <pr_url> --diff

# Same as above, but cap each FIRST/FINAL dump to 2k chars for LLM prompting
uv run scripts/extract_pr_reviews.py <pr_url> --diff --max-file-chars 2000

Workflow

Step 1: Extract with --diff

uv run scripts/extract_pr_reviews.py https://github.com/org/repo/pull/123 --diff

This outputs:

  1. Explicit Suggestions — exact before/after text from suggestion blocks (supports multiple suggestion blocks per comment)
  2. Reviewer Feedback — plain text comments (the "why" behind changes)
  3. File Evolution — first draft and final version of each text file
Tip: add --max-file-chars 2000 to keep each FIRST/FINAL dump lightweight, or pair --diff with --no-files if you only need the suggestion/feedback summaries.

Step 2: Analyze the Output

With the script output, perform this analysis:

A. Catalog the Explicit Suggestions

Create a table of mechanical fixes:

PatternOriginalFixed
Grammar"Its easier""It's easier"
Filler removal"using this way""this way"
Capitalization"Image Generation""image generation"
B. Map Feedback to Changes

For each reviewer feedback comment:

  1. Find the relevant section in FIRST DRAFT
  2. Find the same section in FINAL VERSION
  3. Document what changed and why

Example:

Feedback: "would be nice to end more enthusiastically" First draft: "...it's simple to add new tools to Claude and use them straight away." Final: "...Let us know what you find and create in the comments below!" Lesson: End blog posts with a call-to-action
C. Paragraph-by-Paragraph Comparison

Compare FIRST DRAFT to FINAL VERSION section by section:

  • What was added?
  • What was removed?
  • What was reworded?
  • What structural changes were made?
D. Synthesize Style Patterns

Group findings into categories:

CategoryPatterns Found
ClarityPassive→active, shorter sentences, remove filler
PrecisionVague→specific, "Create"→"Generate"
ToneAdded enthusiasm, call-to-action endings
StructureAdded transitions, better section flow
Grammarits/it's, subject-verb agreement
ContentAdded links, examples, context

Script Options

📁 All paths are relative to the directory containing this SKILL.md file.
FlagOutputUse Case
*(none)*Suggestions + feedbackQuick review of what reviewers said
--diffAdds FIRST/FINAL file dumps to the default outputDeep analysis of how the author responded
--max-file-chars NTruncates each FIRST/FINAL block to *N* chars (appends ...[truncated X chars])Keep prompts within LLM token limits
--no-filesSuppresses FIRST/FINAL dumps even when --diff is setWhen you only need explicit suggestions + reviewer feedback
--jsonRaw JSON (includes file_evolutions when --diff without --no-files)Programmatic processing
Input formats: pass either a full PR URL, owner/repo PR_NUMBER, or owner repo PR_NUMBER.

Output Structure

Default Output

  • Writing Suggestions: Grouped by reviewer, shows original→suggested text (fenced blocks) along with any reviewer note and a permalink back to GitHub
  • Reviewer Feedback: Plain comments without code suggestions, each tagged with its GitHub link

With --diff

  • Explicit Suggestions: Compact before/after pairs, reviewer notes, and GitHub permalinks in one place
  • Reviewer Feedback: Numbered list of requests (same as default view)
  • File Evolution: FIRST DRAFT and FINAL VERSION for each .md/.txt/.rst/.mdx file; add --max-file-chars to truncate each block with a visible ...[truncated X chars] indicator

Handling File Renames

The script traces files through renames by:

  1. Checking each commit for rename operations
  2. Building a path history (e.g., claudeimages.md → claude-images.md → claude-and-mcp.md)
  3. Fetching content using the correct path for each commit

Example Analysis Output

After running the script and performing LLM analysis, produce a summary like:

## Style Lessons from PR #123

### Mechanical Fixes

- Fix grammar: "Its" → "It's" (contraction)
- Lowercase generic terms: "Image Generation" → "image generation"
- Remove filler: "the output quality of" → "the quality of"

### Reviewer-Driven Changes

- **"end more enthusiastically"** → Added call-to-action in conclusion
- **"emphasize these are SoTA"** → Changed "latest" to "state-of-the-art"
- **"add blurb about MCP Server"** → Added explanatory paragraph

### Structural Improvements

- Added transition sentence between sections
- Simplified setup instructions (3 sentences → 1)
- Added new bullet point for model flexibility

Limitations

  • Only extracts inline PR review comments (not issue comments or the PR description)
  • Extremely long files can still be heavy; when that happens, lower --max-file-chars or pass --no-files to keep outputs prompt-friendly

{{currentDate}} {{env}}

平台分布

Codex

36.7%
按下载量换算76

Claude

29.47%
按下载量换算61

Cursor

20.4%
按下载量换算42

Gemini CLI

10.23%
按下载量换算21

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

未通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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