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Agent Skill · 研究检索

seo-aeo(SEO AEO 搜索)

seo-aeo 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。

seo-aeo 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,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 70,176。

总安装 212周安装 9GitHub Stars 28下载 74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:seo-aeo(SEO AEO 搜索)
来源仓库:https://github.com/mangollc/claude-seo-skill
仓库路径:skills/seo-aeo
安装命令:
npx skills add https://github.com/mangollc/claude-seo-skill --skill seo-aeo
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/mangollc/claude-seo-skill --skill seo-aeo

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。

seo-aeo 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词或任务场景快速定位结果。它可协助 Agent 按来源线索组织候选信息。使用时需结合来源仓库、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。seo-aeo 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/seo-aeo

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/mangollc/claude-seo-skill --skill seo-aeo;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

    它需要需要联网,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

seo-aeo 怎么安装?

在终端执行 npx skills add https://github.com/mangollc/claude-seo-skill --skill seo-aeo。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

seo-aeo 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。

seo-aeo 需要什么权限?

权限级别是需要联网。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。

seo-aeo 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。

seo-aeo 用的人多吗?

公开数据是累计安装 212 次,近一周安装 9 次,下载 74 次,GitHub 28 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。

seo-aeo 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

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
seo-aeo

SEO AEO 搜索 · 本页

21228需要联网未明确有提醒

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

AI Search Optimization (AEO)

Load client context first. See seo-keywords rules/client-setup.md.

File Organization

aeo/
├── ai-overview-audit-{date}.json     # Google AI Overview analysis
├── perplexity-audit-{date}.json      # Perplexity citation analysis
├── entity-optimization.json          # Entity and authority audit
├── brand-serp-{date}.json            # Brand SERP analysis
├── structured-data-audit.json        # AI-focused schema audit
├── enhance-aeo-{date}.json           # Enhanced AEO discovery results
├── question-master-list.json         # All discovered questions (deduplicated)
├── ai-visibility-scorecard.json      # Keyword-by-keyword AI test results
├── aeo-checklist-results/
│   └── {url-slug}-aeo.json           # Per-page AEO scores
└── .firecrawl/
    ├── paa-*.json                    # People Also Ask results
    ├── auto-*.json                   # Autocomplete mining results
    ├── reddit-*.json                 # Reddit question mining results
    ├── quora-*.json                  # Quora question mining results
    ├── atp-*.json                    # AnswerThePublic-style question map
    └── ai-test-*.json                # AI visibility test results

Understanding AI Search Engines

Google AI Overviews

  • Appears at top of Google search results for informational queries
  • Synthesizes information from multiple sources
  • Cites sources with links — being cited drives traffic
  • Favors: well-structured content, direct answers, authoritative sources, recent data

Perplexity

  • AI-powered answer engine that cites sources inline
  • Prioritizes: factual accuracy, well-structured content, source diversity, clear attribution
  • Being the definitive source for niche topics is key
  • Structured data and clear headings improve extraction

ChatGPT / Bing

  • ChatGPT with browsing can cite web sources
  • Bing powers much of the web search integration
  • Entity signals (Wikipedia, Wikidata) strongly influence answers
  • Brand recognition and authority matter heavily

Google AI Overview Optimization

Step 1: Identify AI Overview Queries

# Search target keywords and check for AI Overview presence
firecrawl search "{target-keyword}" --scrape --limit 5 -o .seo/clients/{slug}/aeo/.firecrawl/aio-{slug}.json --json

Check search results for AI Overview indicators. Not all queries trigger AI Overviews — focus on those that do.

Step 2: Analyze Cited Sources

For queries where AI Overviews appear, identify which sources get cited:

Common traits of AI Overview sources:

  • Direct answer to the query in the first 1-2 sentences
  • Well-structured with clear H2/H3 headings
  • Uses lists, tables, and structured formats
  • Contains specific data, statistics, or facts
  • Has proper schema markup (FAQPage, HowTo, Article)
  • Is from a recognized authoritative domain
  • Content is recent and up-to-date
  • Uses concise, factual language (not marketing fluff)

Step 3: Optimize Content for AI Citation

For each target page:

  1. Lead with the answer: First 50 words should directly answer the likely query
  2. Use definition format: "X is Y that Z" for concept queries
  3. Structure for extraction: Use H2 headings that match common questions
  4. Include data: Statistics, percentages, specific numbers are preferred
  5. Add comparison tables: AI loves structured data it can reference
  6. Keep paragraphs short: 2-3 sentences max for easy extraction
  7. Use authoritative language: Cite sources, link to studies, reference standards

Perplexity Citation Optimization

What Perplexity Prioritizes

  • Factual accuracy: verifiable claims with sources
  • Comprehensive coverage: thorough treatment of the topic
  • Clear structure: headings, lists, tables that make extraction easy
  • Source credibility: established domains with good reputation
  • Unique information: original data, research, or perspectives
  • Recency: up-to-date content with current data

Optimization Tactics

  1. Become the definitive source: For niche topics, create the most comprehensive resource
  2. Original data: Publish surveys, studies, or data analysis that others cite
  3. FAQ format: Question-and-answer format maps directly to how Perplexity answers queries
  4. Entity clarity: Make it unambiguous what entity/brand/concept the content is about
  5. Cross-reference: Link to authoritative sources to build credibility
  6. Update frequency: Keep content fresh with regular updates and current year references

ChatGPT / Bing Optimization

Bing SEO Fundamentals

Bing weighs some factors differently than Google:

  • Exact-match keywords: Bing is more keyword-literal than Google
  • Social signals: Bing considers social media activity more
  • Multimedia: Bing favors pages with images and video
  • Domain age: Established domains get more credit
  • Official sources: Bing strongly favors.gov,.edu, and Wikipedia

Entity Signals for ChatGPT

ChatGPT's knowledge includes entities from:

  • Wikipedia: Having a Wikipedia page significantly increases brand/entity recognition
  • Wikidata: Structured entity data feeds into AI knowledge bases
  • Social profiles: Consistent entity data across LinkedIn, Twitter/X, Crunchbase
  • News coverage: Press mentions train AI models on brand associations
  • Schema.org Organization: sameAs links to all official profiles

Action items:

  1. Check if brand/founder has a Wikipedia page (if notable enough to qualify)
  2. Verify Wikidata entry exists and is accurate
  3. Ensure consistent brand information across all platforms
  4. Build press coverage and news mentions
  5. Implement Organization schema with comprehensive sameAs links

Structured Data for AI Consumption

Beyond standard SEO schema, these types specifically help AI extraction:

FAQPage Schema

Most impactful for AEO — provides direct Q&A pairs AI can quote:

{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is {topic}?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Concise, direct answer here. {topic} is..."
      }
    }
  ]
}

HowTo Schema

Step-by-step instructions AI can present directly:

{
  "@context": "https://schema.org",
  "@type": "HowTo",
  "name": "How to {do thing}",
  "step": [
    { "@type": "HowToStep", "name": "Step title", "text": "Step description" }
  ]
}

DefinedTerm Schema

For glossary/definition content AI frequently references:

{
  "@context": "https://schema.org",
  "@type": "DefinedTerm",
  "name": "Term Name",
  "description": "Clear definition of the term"
}

Speakable Property

Mark content suitable for voice assistants:

{
  "@context": "https://schema.org",
  "@type": "Article",
  "speakable": {
    "@type": "SpeakableSpecification",
    "cssSelector": [".article-summary", ".key-takeaway"]
  }
}

Organization with Comprehensive sameAs

Link all brand profiles for entity recognition:

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "{brand}",
  "url": "{domain}",
  "sameAs": [
    "https://www.linkedin.com/company/{brand}",
    "https://twitter.com/{brand}",
    "https://www.facebook.com/{brand}",
    "https://www.youtube.com/{brand}",
    "https://en.wikipedia.org/wiki/{brand}",
    "https://www.wikidata.org/wiki/{entity_id}",
    "https://www.crunchbase.com/organization/{brand}"
  ]
}

FAQ & Entity Optimization

People Also Ask (PAA) Mining

# Search target queries to find PAA questions
firecrawl search "{topic} FAQ" --scrape --limit 10 -o .seo/clients/{slug}/aeo/.firecrawl/paa-{slug}.json --json
firecrawl search "what is {topic}" --scrape --limit 5 -o .seo/clients/{slug}/aeo/.firecrawl/whatis-{slug}.json --json
firecrawl search "how does {topic} work" --scrape --limit 5 -o .seo/clients/{slug}/aeo/.firecrawl/howdoes-{slug}.json --json

Collect PAA questions and create content that:

  1. Uses the exact question as an H2 heading
  2. Answers directly in the first sentence below the heading
  3. Expands with 2-3 supporting sentences
  4. Wraps in FAQPage schema

Entity-First Writing Style

  • Define entities clearly on first mention
  • Use consistent terminology (don't switch between "AI search" and "answer engines" randomly)
  • Link entities to their canonical references
  • Use structured data to disambiguate entities

Brand Authority Signals Audit

Check these authority indicators:

SignalHow to CheckStatus
Wikipedia pagefirecrawl search "{brand} wikipedia" --limit 3Present / Absent / Stub
Wikidata entryfirecrawl search "wikidata {brand}" --limit 3Present / Absent
Knowledge Panelfirecrawl search "{brand}" --limit 5 — check for KP in resultsTriggered / Not triggered
Social profiles verifiedCheck LinkedIn, Twitter/X, Facebook, YouTubeAll present / Gaps
News coveragefirecrawl search "{brand}" --sources news --limit 10Recent / Stale / None
Industry mentionsfirecrawl search "{brand} {industry}" --limit 10Strong / Moderate / Weak
Schema OrganizationScrape homepage for Organization schemaPresent / Incomplete / Missing
sameAs linksCheck if Organization schema links to all profilesComplete / Incomplete

Brand SERP Management

Analyze what appears when someone searches the brand name:

firecrawl search "{brand_name}" --scrape --limit 20 -o .seo/clients/{slug}/aeo/.firecrawl/brand-serp.json --json

Audit the First Page

For each result on page 1 of brand search:

PositionURLTypeSentimentOwned?
1example.comHomepagePositiveYes
2linkedin.com/company/...SocialPositiveYes
3yelp.com/biz/...ReviewMixedNo (but manageable)
...............

Goals:

  • Own positions 1-5 with: homepage, social profiles, blog, about page
  • Monitor positions 6-10: review sites, press, directories
  • Flag negative results and develop strategy to push them down
  • Ensure Knowledge Panel is accurate and complete

Brand SERP Optimization

  1. Claim and optimize all social profiles: LinkedIn, Twitter/X, Facebook, YouTube, Instagram, Pinterest, TikTok (whichever are relevant)
  2. Optimize for branded keywords: Ensure homepage title includes brand name, about page ranks for "about {brand}"
  3. Review management: Respond to all reviews, encourage positive reviews to improve review site listings
  4. Press and PR: Create newsworthy content that generates branded press mentions
  5. Knowledge Panel: Submit edits via Google if panel exists, build entity signals if it doesn't

Per-Page AEO Checklist

For each important page, score against these AI-readiness factors:

FactorCheckPoints
Direct answer in first 50 wordsDoes the opening directly answer the target query?15
FAQ section presentAre there Q&A pairs on the page?10
FAQPage schemaIs FAQ content wrapped in JSON-LD?10
Clear entity markupOrganization/Person/Product schema present?10
Structured data (lists/tables)Does the page use lists and tables for key data?10
Concise definitionsAre key terms defined clearly?10
Authoritative sources citedDoes content link to studies, official sources?10
Author byline with credentialsIs there a named, credible author?10
Updated date visibleDoes the page show a recent update date?5
speakable content markedIs key content marked for voice assistants?5
sameAs links on entity pagesDo brand/person pages link to all profiles?5

Total: 100 points

Grade: A (85-100), B (70-84), C (55-69), D (40-54), F (< 40)


Enhanced AEO Discovery (AI Question Discovery)

The /enhance-aeo command runs 5 deep-discovery modules to find what real people are asking AI engines about your topic, and tests how visible you are in AI-generated answers. No API keys needed — uses Firecrawl search to mine publicly available data.

Why This Matters

LLMs learn from and cite the same content that appears in:

  • Google's "People Also Ask" boxes
  • Google autocomplete suggestions
  • Reddit threads and Quora answers
  • FAQ-style content across the web

By mining these sources, you discover the exact questions people ask AI chatbots — and can create content that AI engines will cite.

Module 1: People Also Ask (PAA) Chain Mining

PAA questions are the strongest proxy for LLM queries. Google shows these because people commonly ask them — the same people then ask ChatGPT, Perplexity, etc.

Search patterns:

  • {keyword} — direct PAA boxes
  • what is {keyword} — definitional questions
  • how to {keyword} — procedural questions
  • why {keyword} — reasoning questions
  • {keyword} vs — comparison questions

Extract and deduplicate all PAA questions, group by intent.

Module 2: Google Autocomplete Mining

Autocomplete reflects real-time search behavior. Patterns:

  • {keyword} + [a, how, best, for, can, should, is]

Cross-reference with PAA results — overlapping questions are highest priority.

Module 3: Reddit & Quora Question Mining

These platforms are where real people ask real questions in natural language — the same format they use with AI chatbots. LLMs are also trained on this data.

Search patterns:

  • site:reddit.com {keyword} — Reddit threads
  • site:quora.com {keyword} — Quora questions
  • reddit {keyword} recommendations — Purchase intent
  • reddit best {keyword} — Comparison intent

Extract: thread titles (= questions), top-voted answers (= what AI learns from), brand mentions, pain points, decision criteria.

Module 4: AnswerThePublic-Style Question Mapping

Build a complete question tree using all question word variations:

  • who, what, when, where, which, without, with, near me

Creates a visual question map showing all angles people approach the topic from.

Module 5: Automated AI Visibility Testing

Systematically test each of the client's top keywords (up to 20):

For each keyword:

  1. Search via Firecrawl, check results for AI Overview presence
  2. Check if client is cited in AI features
  3. Identify which competitors ARE cited
  4. Scrape top-cited competitor pages
  5. Reverse-engineer WHY they get cited (structure, schema, depth, FAQ sections, author credentials)

Output an AI Visibility Scorecard:

KeywordAI Overview?You Cited?Top CitedGap
kw1Yes/NoYes/NocompetitorHigh/Med/Low

Master Question List

After all 5 modules complete, compile a deduplicated master list:

  • Total unique questions across all sources
  • Ranked by frequency (appeared in multiple modules = higher priority)
  • Tagged with source: PAA, Autocomplete, Reddit, Quora, Question Map
  • Tagged with intent: Informational, Commercial, Navigational, Transactional
  • Tagged with status: Answered on your site / Not answered / Partially answered

Action Plan Output

  1. Top 10 questions to create content for (highest frequency, not yet answered)
  2. Top 5 existing pages to restructure for AI citation
  3. Schema markup additions needed
  4. Content gaps where competitors dominate AI results
  5. Reddit/Quora communities to participate in for brand visibility

平台分布

Codex

33.11%
按下载量换算25

Claude

28.4%
按下载量换算21

Cursor

20.97%
按下载量换算16

Gemini CLI

9.34%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

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。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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