Agent skill

Content Review

by ranxi2001 in ranxi2001/zero2Agent

审查 zero2Agent 项目中的文章内容质量。当用户说"审查文章"、"review内容"、"检查这篇文章写得怎么样"、"看看这篇符不符合项目风格"、"帮我看看内容质量"时触发。负责对照项目风格标准进行结构化评审,输出具体的改进建议。即使用户只是说"帮我看看写得怎么样",只要涉及 zero2Agent 的 Markdown 文章,也应当触发此技能。

MITAuto-check passed

Install Content Review

skills CLI
$ npx skills add ranxi2001/zero2Agent --skill content-review -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ranxi2001/zero2Agent content-review --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ranxi2001/zero2Agent.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/content-review .claude/skills/content-review && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
content-review
GitHub stars
703
Token cost
~385 tokens
SKILL.md length
80 words
Files
1
Skills in repo
8
Repo updated
First seen
Licence
MIT

At a glance

审查 zero2Agent 项目中的文章内容质量。当用户说"审查文章"、"review内容"、"检查这篇文章写得怎么样"、"看看这篇符不符合项目风格"、"帮我看看内容质量"时触发。负责对照项目风格标准进行结构化评审,输出具体的改进建议。即使用户只是说"帮我看看写得怎么样",只要涉及 zero2Agent 的 Markdown 文章,也应当触发此技能。

  • Works in 7 steps: Frontmatter 完整性 → 开篇质量(问题优先) → 工程视角 → …
  • SKILL.md covers 审查维度(7 项), 输出格式 and 执行步骤
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Content Review is an agent skill from ranxi2001/zero2Agent. 审查 zero2Agent 项目中的文章内容质量。当用户说"审查文章"、"review内容"、"检查这篇文章写得怎么样"、"看看这篇符不符合项目风格"、"帮我看看内容质量"时触发。负责对照项目风格标准进行结构化评审,输出具体的改进建议。即使用户只是说"帮我看看写得怎么样",只要涉及 zero2Agent 的 Markdown 文章,也应当触发此技能。

Its SKILL.md is about 390 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: 面向大厂Agent研发岗位求职的agent教程网站,涵盖技术路线与面试八股文. The licence is MIT.

Example prompts

  • “review内容”
  • “检查这篇文章写得怎么样”
  • “看看这篇符不符合项目风格”
  • “/content-review”

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Frontmatter 完整性
  2. 开篇质量(问题优先)
  3. 工程视角
  4. 避免框架崇拜
  5. 暴露真实复杂度
  6. 语言和结构
  7. 文末导航

What it can do on your machine

Read from SKILL.md and the folder at commit 472ce78. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Content Review loads about 385 tokens when it runs. Until then it costs about 48 tokens; SKILL.md has 80 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~48
When it runs · the whole SKILL.md, loaded when a task matches
~385

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ranxi2001/zero2Agent at commit 472ce78, republished under its MIT licence (© ranxi2001). 80 words, ~385 tokens.

Download SKILL.mdSave it as .claude/skills/content-review/SKILL.md (or your agent's skills folder).
name
content-review
description
审查 zero2Agent 项目中的文章内容质量。当用户说"审查文章"、"review内容"、"检查这篇文章写得怎么样"、"看看这篇符不符合项目风格"、"帮我看看内容质量"时触发。负责对照项目风格标准进行结构化评审,输出具体的改进建议。即使用户只是说"帮我看看写得怎么样",只要涉及 zero2Agent 的 Markdown 文章,也应当触发此技能。

content-review:文章内容审查

本技能用于对 zero2Agent 项目中的 Markdown 文章进行结构化质量审查。

审查维度(7 项)

1. Frontmatter 完整性
  • layout: default 是否存在
  • title、description、eyebrow 是否均已填写
  • eyebrow 格式是否正确(如 Agent Basic / 05)
  • description 长度是否在 10–30 字之间
2. 开篇质量(问题优先)
  • 开头是否先说"为什么这个问题值得关注",而非直接给定义
  • 是否引出了读者可能有的误解或常见困惑
  • 前 3 段是否能让读者产生"这跟我有关"的感觉
3. 工程视角
  • 概念解释是否落脚到"它在系统里扮演什么角色"
  • 是否有具体的系统行为描述,而不只是抽象定义
  • 是否提到了真实工程场景中的约束或权衡
4. 避免框架崇拜
  • 是否出现了对某个框架的无条件推荐
  • 每次提到框架时是否说明了"它解决什么问题"和"它的代价"
  • 是否有"X 是最佳实践"这类不加论证的断言
5. 暴露真实复杂度
  • 是否主动提到了容易踩坑的地方
  • 是否区分了"Demo 能跑"和"生产可用"的差距
  • 是否对失败场景有基本描述
6. 语言和结构
  • 全文是否使用中文(代码块、路径、专有名词除外)
  • 段落是否简洁,避免废话和修饰语堆砌
  • 是否合理使用了 # ## ### 标题层级
  • 是否合理使用了代码块(text 或具体语言)展示流程/示例
7. 文末导航
  • 是否有"下一篇建议继续看:"的链接
  • 链接路径是否使用相对路径 + index.html

输出格式

审查结果按如下结构输出:

## 审查报告:{文章标题}

**整体评分**:✅ 通过 / ⚠️ 需改进 / ❌ 有明显问题

### 1. Frontmatter 完整性
状态:✅ / ⚠️ / ❌
说明:{具体发现,若通过则简写"符合要求"}

### 2. 开篇质量
状态:…
说明:…

### 3. 工程视角
…(以此类推)

---

## 改进建议

{按优先级排列的具体修改建议,每条说明原因}

1. **[高优先级]** {问题描述} → 建议:{具体怎么改}
2. **[中优先级]** …
3. **[低优先级]** …

执行步骤

  1. 定位文章:如果用户没有指定路径,根据对话上下文判断要审查哪篇文章。如果不明确,询问用户。

  2. 读取文章:用 Read 工具读取对应的 index.md。

  3. 逐维度审查:按上述 7 个维度逐一检查,记录发现。

  4. 输出报告:按输出格式生成报告,改进建议要具体到"第几段、哪句话、怎么改",不要泛泛而谈。

  5. 可选:批量审查:如果用户要求审查整个模块,依次读取所有文章并汇总报告,最后给出模块级别的总结(哪些维度普遍偏弱)。

© ranxi2001, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agents/skills/content-review of ranxi2001/zero2Agent.

Open the folder on GitHubat commit 472ce78

Compare with similar skills

Content Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Content Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Content Review this skillranxi2001/zero2Agent703—~385Automated safety check: PassMIT
Prompt Optimizeraffaan-m/ECC276k2 repos~2.4kAutomated safety check: PassMIT
Zsxq Replyitwanger/toBeBetterJavaer18k—~979Automated safety check: PassNone
Video Syncitwanger/toBeBetterJavaer18k—~445Automated safety check: PassNone
Generate StoryboardArcReel/ArcReel5.4k—~816Automated safety check: PassAGPL-3.0
Good Askdigoal/blog8.6k—~723Automated safety check: PassGPL-2.0

Similar skills

  • Prompt Optimizer

    affaan-m/ECC

    分析原始提示,识别意图和差距,匹配ECC组件(技能/命令/代理/钩子),并输出一个可直接粘贴的优化提示。仅提供咨询角色——绝不自行执行任务。触发时机:当用户说“优化提示”、“改进我的提示”、“如何编写提示”、“帮我优化这个指令”或明确要求提高提示质量时。中文等效表达同样触发:“优化prompt”、“改进prompt”、“怎么写prompt”、“帮我优化这个指令”。不触发时机:当用户希望直接执行任…

    276k GitHub starsUsed in 2 repos~2.4k tokens
    DevelopmentAuto-check passed
  • Zsxq Reply

    itwanger/toBeBetterJavaer

    以二哥(沉默王二)的身份回复知识星球「Java进阶之路&二哥编程星球」的帖子、提问和评论。完整工作流:扫描未回复的球友提问 → 参照二哥历史回复出草稿 → 用户确认后通过 zsxq-cli 发布。当用户说"看看星球有没有没回的提问"、"回复星球"、"星球回帖"、"帮我回答球友的问题"、"星球提问",或给出某条星球帖子链接/ID 要求回复时,必须使用此…

    18k GitHub stars~979 tokensUpdated yesterday
    Auto-check passed
  • Video Sync

    itwanger/toBeBetterJavaer

    把「王二讲Agent」的 B 站视频链接同步到 docs/src/ai/video/readme.md,把抖音视频 ID 同步到 docs/src/.vuepress/agentInterview.ts 的 douyinVideoIds 映射表(页面会渲染成播放器)。当用户说 B 站更新了、抖音更新了、同步视频链接、把视频地址放进脚本、更新 readme 视频时使用。

    18k GitHub stars~445 tokensUpdated yesterday
    DevelopmentAuto-check passed
  • Generate Storyboard

    ArcReel/ArcReel

    为分镜生成分镜图。当用户说"生成分镜"、"预览分镜画面"、想重新生成某些分镜图、或剧本中有分镜缺少分镜图时使用。自动保持角色和画面连续性。

    5.4k GitHub stars~816 tokensUpdated today
    Media & CreativeAuto-check passed
  • Good Ask

    digoal/blog

    给定一个行业(如新能源汽车、预制菜、少儿编程、殡葬、货运物流),提出若干个"好问题"——不作解答,但给出扎实理由。好问题指行业老大难或近期热点、真实不虚构、牵连广泛、深刻难解、够得着有解法、且有讨论张力。当用户说"针对X行业提几个好问题""这个行业有哪些值得深挖的真问题""帮我找选题/议题/讨论话题""这行的痛点/争议是什么"时使用本技能。

    8.6k GitHub stars~723 tokensUpdated today
    Auto-check passed
  • Generate Grid

    ArcReel/ArcReel

    生成宫格分镜图。当用户说"生成宫格"、"宫格生图"、"用宫格装配生成分镜"时使用。自动按 segmentbreak 分组,选择最优宫格大小,生成链式过渡帧宫格联合图;用户审阅联合图并同意后,再切分落格为各分镜的起始分镜图。

    5.4k GitHub stars~495 tokensUpdated today
    Media & CreativeAuto-check passed

More from ranxi2001/zero2Agent

All 8 skills in this repo
  • Drawio Skill

    ranxi2001/zero2Agent

    A skill your agent uses when user requests diagrams, flowcharts, architecture charts, or visualizations.

    703 GitHub stars~6.6k tokensUpdated today
    Auto-check passed
  • Classify Interview Questions

    ranxi2001/zero2Agent

    将批量面经或零散面试题逐题去重并分发:Agent/LLM/AI工程题写入 zero2Agent 的 learn-agent-interview,传统后端八股写入相邻 zero2Leetcode 的夏季八股。大批量输入使用 gpt-5.6-luna API 逐篇并发抽题和语义召回,再审查、去重和写答案;不新建面经实录文章。

    703 GitHub stars~2.6k tokensUpdated today
    Auto-check passed
  • Chinese Quotes Fix

    ranxi2001/zero2Agent

    Check and fix Chinese quote pairing in Markdown files generated by ClaudeCode or other agents, while preserving Markdown syntax and protected blocks.

    703 GitHub stars~735 tokensUpdated today
    Auto-check passed
  • New Article

    ranxi2001/zero2Agent

    在 zero2Agent 项目中创建新的学习文章。当用户说"写一篇新文章"、"创建文章"、"新建文章"、"在某模块下添加一篇关于X的文章"、"帮我起草一篇讲XX的内容"、"整理面经"时触发。适用于所有模块下新建内容,包括面试维度拆解文章和面经实录。即使用户没有明确说"文章",只要涉及给 zero2Agent 项目增加教学内容,也应当触发此技能。

    703 GitHub stars~693 tokensUpdated today
    Auto-check passed
  • New Module

    ranxi2001/zero2Agent

    在 zero2Agent 项目中创建新的学习模块。当用户说"新建模块"、"添加模块"、"创建一个新的学习章节"、"我想增加一个关于X的模块"时触发。负责创建模块目录结构、index.md,并同步更新主页 index.html 和 layouts/default.html 的导航。即使用户只是说"我想增加一个讲XX的章节",也应当触发此技能。

    703 GitHub stars~489 tokensUpdated today
    Auto-check passed
  • Scrape Nowcoder

    ranxi2001/zero2Agent

    基于 CDP 原生 WebSocket 抓取牛客网面经文章。当用户说"抓牛客"、"爬牛客面经"、"nowcoder 抓取"、"抓取面经列表"时触发。通过 Chrome 调试端口直接连接已登录的浏览器会话,支持首页、话题、搜索分页和详情全文抓取,输出 Markdown。

    703 GitHub stars~1.7k tokensUpdated today
    Auto-check passed

Questions about Content Review

What does Content Review do?

审查 zero2Agent 项目中的文章内容质量。当用户说"审查文章"、"review内容"、"检查这篇文章写得怎么样"、"看看这篇符不符合项目风格"、"帮我看看内容质量"时触发。负责对照项目风格标准进行结构化评审,输出具体的改进建议。即使用户只是说"帮我看看写得怎么样",只要涉及 zero2Agent 的 Markdown 文章,也应当触发此技能。. Content Review is an agent skill from ranxi2001/zero2Agent.

How do I install Content Review in Claude Code?

Run `npx skills add ranxi2001/zero2Agent --skill content-review -a claude-code`. Or copy the skill folder (.agents/skills/content-review in ranxi2001/zero2Agent) into .claude/skills/content-review in your project. Claude Code loads it when a task matches its description.

How do I install Content Review in Codex?

Run `npx skills add ranxi2001/zero2Agent --skill content-review -a codex`. Or copy the skill folder (.agents/skills/content-review in ranxi2001/zero2Agent) into .agents/skills/content-review in your project. Codex loads it when a task matches its description.

Can I use Content Review in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ranxi2001/zero2Agent --skill content-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/content-review, .gemini/skills/content-review, .github/skills/content-review and .opencode/skills/content-review in your project.

What does Content Review need to run?

SKILL.md names no scripts, command-line tools or credentials: Content Review is instructions for the agent only.

Does Content Review access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Content Review safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Content Review use?

Content Review is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Content Review use?

About 385 tokens (SKILL.md is roughly 1.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Content Review?

Skills that share tags, products or a category with Content Review: Prompt Optimizer (affaan-m/ECC, 276k stars), Zsxq Reply (itwanger/toBeBetterJavaer, 18k stars), Video Sync (itwanger/toBeBetterJavaer, 18k stars) and Generate Storyboard (ArcReel/ArcReel, 5.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Content Review?

ranxi2001 (a GitHub user) maintains it in ranxi2001/zero2Agent, which has 703 GitHub stars. The repository holds 8 skills in this directory. The repository was last updated on October 9, 2026.

Source: ranxi2001/zero2Agent on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.