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Agent Skill · 研究检索

content-optimization(内容优化)

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。

content-optimization 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为只读;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 18,846。

总安装 5,880周安装 250GitHub Stars 公开资料未说明下载 2,060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
MIT-0
版本
1.2.1

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:content-optimization(内容优化)
来源仓库:https://github.com/kostja94/content-optimization
安装命令:
openclaw skills install content-optimization
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install content-optimization

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。

content-optimization 辅助优化 SEO 文案,提升字数、H2 关键字密度、多媒体嵌入与列表结构合理性。适用于撰写博客、产品页或营销材料时增强搜索引擎可见性。提供可读性评分与关键词分布热力图反馈,指导内容迭代方向。不替代人工审核,建议结合品牌调性做最终润色调整。

适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。

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 OpenClaw;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 openclaw skills install content-optimization;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

content-optimization 怎么安装?

在终端执行 openclaw skills install content-optimization。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

content-optimization 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

content-optimization 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

content-optimization 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

content-optimization 用的人多吗?

公开数据是累计安装 5,880 次,近一周安装 250 次,下载 2,060 次。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。

content-optimization 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 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 OpenClaw,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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 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
content-optimization

内容优化 · 本页

5,880—只读MIT-0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

name
content-optimization
description
When the user wants to optimize content for SEO—word count, H2 keywords, keyword density, multimedia, tables, lists. Also use when the user mentions "content length," "word count," "keyword stuffing," "H2 keywords," "keyword density," "tables," "bullet points," or "content structure." For keywords, use keyword-research.
metadata
version
1.2.1

SEO Content: Content Optimization

Guides on-page content optimization: word count, heading keywords, keyword density vs stuffing, multimedia, tables, and lists. Complements heading-structure (structure) and content-strategy (planning).

When invoking: On first use, if helpful, open with 1–2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output.

Scope

  • Word count: For articles, see article-content (word count by type). This skill covers generic content length strategy.
  • H2 keywords: Placement, quantity, variation
  • Keyword density vs stuffing: Natural use; avoid manipulation
  • Multimedia: Images, tables, lists, video for structure and Featured Snippets. See featured-snippet for snippet-specific optimization; video-optimization for video SEO.

Initial Assessment

Check for project context first: If .claude/project-context.md or .cursor/project-context.md exists, read it for target keywords and content type.

Identify:

  1. Content type: Article, guide, listicle, pillar, news
  2. Target keyword: Primary and secondary
  3. Competitors: Top 10 average length and structure — see competitor-research

Word Count

Google does not rank by word count. Length should match search intent and topic depth. A 1,000-word post that satisfies intent can outrank a 3,000-word thin piece.

Reference Ranges by Content Type

For article word count by type (news, how-to, listicle, pillar, etc.), see article-content. Generic ranges:

Content typeWord countNotes
News / announcements300–600Time-sensitive; concise
Standard articles / how-tos1,000–1,500Single topic; actionable
Listicles / guides1,200–2,000"Top 10," "Best X"
Pillar / cornerstone2,000–3,500+Comprehensive; cluster hub

Strategy

  1. Analyze top 10 for target keyword — average length and depth
  2. Match intent — informational often needs ~40% longer than transactional
  3. Value over padding — each section must add genuine value; avoid fluff
  4. Comprehensive coverage — answer the query and related questions

H2 Heading Keywords

Placement

  • Primary keyword: Include naturally in at least one H2 when relevant
  • Related keywords: Use LSI and long-tail in other H2s for topical coverage
  • Avoid stuffing: Headings must stay clear and readable; organic placement only

Quantity

  • No strict limit — one H2 per major section; structure follows content
  • Typical article: 4–8 H2s; pillar: 8–15+ H2s
  • Hierarchy: H1 → H2 (major sections) → H3 (subsections); don't skip levels

Best Practices

PracticePurpose
Descriptive H2sSearch engines understand context; users scan
Answer-firstPlace direct answer in first 40–50 words after H2 for Featured Snippets; see featured-snippet
Keyword variationUse related terms; avoid repeating exact phrase in every H2
Logical flowH2s outline the article; support topical authority

Keyword Density vs Keyword Stuffing

Definitions

TermMeaning
Keyword density(Keyword count / Total words) × 100; a metric, not a ranking factor
Keyword stuffingExcessive, unnatural repetition to manipulate rankings; black-hat

Current Guidance

  • Keyword density is not a direct ranking factor — Google has stated since 2011 that repetition alone doesn't improve rankings
  • Reference range: 0.5%–1.5% for most content; some sources cite up to 2.5%
  • Use density mainly to avoid stuffing — if density exceeds ~2–3% and reads unnaturally, reduce
  • Prioritize natural placement: title, H1, first 100 words, 1–2 H2s, body; avoid forced repetition

How to Avoid Stuffing

  • Write for users first; keywords should fit naturally
  • Use synonyms, related terms, and question phrasing
  • If a sentence sounds awkward with the keyword, rewrite
  • Monitor: if every paragraph repeats the exact phrase, simplify

Multimedia: Images, Tables, Lists

Images

PracticePurpose
Alt, file names, captionsSee image-optimization for full image SEO (alt, format, responsive, lazy loading, image sitemap, LCP, captions for Featured Snippets)
Original over stockUnique images signal E-E-A-T — see eeat-signals

Content placement: Put images near relevant text; captions support snippet thumbnails. See image-optimization for captions; featured-snippet for snippet context.

Video

PracticePurpose
Embed + metadataVideoObject schema, video sitemap, thumbnail; see video-optimization
YouTubeGoogle prioritizes YouTube in search; GEO citation; see youtube-seo, generative-engine-optimization
Featured Snippet (video)Video schema; timestamps/chapters; see featured-snippet

Tables

  • Use for: Comparisons, stats, specs, "X vs Y"
  • Semantic HTML: <table>, <thead>, <tbody>, clear column headers
  • Featured Snippets: ~6% of snippets are tables; optimize headers with target keywords. See featured-snippet
  • Mobile: Responsive; avoid horizontal scroll when possible
  • Data quality: No empty cells; consistent units; accurate, current data

Lists: Ordered vs Unordered

TypeUse caseSEO / Snippet
Ordered (<ol>)Steps, rankings, sequences, "Top 10"List snippets (~19% of Featured Snippets); how-to; see featured-snippet
Unordered (<ul>)Non-sequential items, features, optionsBullet snippets; definitions, options

Best practices:

  • Use semantic <ol> and <ul>; avoid divs styled as lists
  • Answer-first: For snippet targets, put the direct answer in the first 40–50 words after the heading
  • Concise items: List items should be scannable; expand in body if needed
  • Logical order: Ordered lists = sequence matters; unordered = no sequence

GEO / AI Citation

Answer-first (direct answer in first 40–60 words after H2) supports both Featured Snippets and GEO. For article-level GEO (TL;DR, Key Takeaways, QAE pattern), see article-content and generative-engine-optimization. For Featured Snippet formats and optimization, see featured-snippet.


Content Audit Checklist

For article content audit (hook, QAE, product connection, CTA, references, gaps), see article-content. This skill covers generic content optimization (H2 keywords, multimedia, keyword density).


Output Format

  • Word count recommendation by content type
  • H2 outline with keyword placement
  • Keyword density check (avoid stuffing)
  • Structure (tables, lists) for Featured Snippet opportunity; see featured-snippet
  • Multimedia checklist (images per image-optimization; tables, lists)

Related Skills

  • heading-structure: H1–H6 hierarchy; H2 keyword placement
  • content-strategy: Topic clusters, pillar + cluster
  • keyword-research: Target keywords inform placement
  • featured-snippet: Snippet formats, structure; answer-first
  • eeat-signals: E-E-A-T; original images, trust
  • image-optimization: Alt, captions, format, LCP, responsive, image sitemap
  • video-optimization: Video SEO; VideoObject; video sitemap
  • competitor-research: Competitor length and structure as reference
  • article-content: Article word count by type; Content Audit Checklist; article body creation

平台分布

OpenClaw

79.85%
按下载量换算1,645

安全审计

VirusTotal

未展示

ClawScan

通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。目前只有一个公开来源,建议同时核对源仓库。

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