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SERP analysis and search intent mapping: analyze ranking factors, SERP features, AI overviews, featured snippets, and People Also Ask patterns. Part of a 20-skill SEO & GEO suite. SERP分析/搜索结果/精选摘要/AI概览/搜索意图
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超级简历 WonderCV 出品，3000 万用户信赖。简历分析、段落改写、JD 岗位匹配、自动匹配职位、PDF 导出、AI 求职导师（面试准备/薪资谈判/职业规划/多版本简历策略）。 触发条件：用户提供简历、要求简历点评/打分/反馈、希望改写某个简历部分、 希望将简历与岗位 JD 匹配、咨询求职建议或面试准备，或提到 CV/简历/求职。 不触发条件：用户讨论普通写作（非简历）、询问其他文档， 或讨论与求职和职业发展无关的话题。
Order food/drinks (点餐) on an Android device paired as an OpenClaw node. Uses in-app menu and cart; add goods, view cart, submit order (demo, no real payment).
调用久吾智能体API进行文本或文件分析处理。支持两种调用方式：(1) 文本内容分析 - 传入name(智能体名称)、docno(文档编号)、content(文本内容)；(2) 文件分析 - 传入name、docno和files(文件列表)进行智能评审。适用于合同评审、需求评审、文档审查等场景。当用户要求评审合同、分析条款、审查文档、需求评审、合同条款分析、或需要对文本和文件进行AI智能分析时触发。
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SKILL.md を表示中
| name | serp-analysis |
| description | SERP analysis and search intent mapping: analyze ranking factors, SERP features, AI overviews, featured snippets, and People Also Ask patterns. Part of a 20-skill SEO & GEO suite. SERP分析/搜索结果/精选摘要/AI概览/搜索意图 |
| version | 6.0.0 |
| license | Apache-2.0 |
| compatibility | Claude Code ≥1.0, skills.sh marketplace, ClawHub marketplace, Vercel Labs skills ecosystem. No system packages required. Optional: MCP network access for SEO tool integrations. |
| allowed-tools | WebFetch |
| homepage | https://github.com/aaron-he-zhu/seo-geo-claude-skills |
| when_to_use | Use when analyzing search engine results pages, SERP features, featured snippets, People Also Ask, or understanding ranking patterns for a query. |
| argument-hint | <keyword or query> |
| metadata | {"author":"aaron-he-zhu","version":"6.0.0","geo-relevance":"high","tags":["seo","geo","serp-analysis","serp-features","featured-snippet","ai-overview","people-also-ask","search-intent","SERP分析","検索結果分析","검색결과","analisis-serp"],"triggers":["analyze search results","SERP analysis","what ranks for","SERP features","why does this page rank","featured snippets","AI overviews","what's on page one for this query","who ranks for this keyword","what does Google show for","what shows up for this search","who is on page one","why does this page rank first","what SERP features appear for","SERP分析","搜索结果分析","精选摘要","AI概览","谁排第一","搜索结果长什么样","谁排在前面","検索結果ページ分析","検索結果分析","強調スニペット","검색 결과 분석","SERP 분석","análisis SERP","análisis de resultados de búsqueda","análise de SERP","serp anaylsis"]} |
Decode any search results page before you write a single word — this skill maps every ranking factor, SERP feature, and AI Overview trigger for your target keyword, then tells you exactly what format and depth your content needs to win.
Quick example: Analyze the SERP for "how to start a podcast" → see which content types dominate, which featured snippets are winnable, whether an AI Overview fires, and the minimum domain authority needed to rank.
System role: Research layer skill. It turns market signals into reusable strategic inputs for the rest of the library.
Part of the SEO & GEO Skills Library · 20 skills · ClawHub · skills.sh
Use this when the conversation involves any of these situations — even if the user does not use SEO terminology:
Use this whenever the task needs reusable market intelligence that should influence strategy, not just an ad hoc answer.
Start with one of these prompts. Finish with a short handoff summary using the repository format in Skill Contract.
Analyze the SERP for [keyword]
What does it take to rank for [keyword]?
Analyze featured snippet opportunities for [keyword list]
Which of these keywords trigger AI Overviews? [keyword list]
Why does [URL] rank #1 for [keyword]?
Expected output: a prioritized research brief, evidence-backed findings, and a short handoff summary ready for memory/research/.
memory/research/.CLAUDE.md, memory/decisions.md, and memory/research/; hand canonical entity work to entity-optimizer.Next Best Skill below when the findings are ready to drive action.Note: All integrations are optional. This skill works without any API keys — users provide data manually when no tools are connected.
See CONNECTORS.md for tool category placeholders.
With ~~SEO tool + ~~search console + ~~AI monitor connected: Automatically fetch SERP snapshots for target keywords, extract ranking page metrics (domain authority, backlinks, content length), pull SERP feature data, and check AI Overview presence using ~~AI monitor. Historical SERP change data and mobile vs. desktop variations can be retrieved automatically.
With manual data only: Ask the user to provide:
Proceed with the full analysis using provided data. Note in the output which metrics are from automated collection vs. user-provided data.
When a user requests SERP analysis:
Understand the Query
Clarify if needed:
Map SERP Composition
Document all elements appearing on the results page: AI Overview, ads, featured snippet, organic results, PAA, knowledge panel, image pack, video results, local pack, shopping results, news results, sitelinks, and related searches.
Analyze Top Ranking Pages
For each of the top 10 results, document: URL, domain, domain authority, content type, word count, publish/update dates, on-page factors (title, meta description, H1, URL structure), content structure (headings, media, tables, FAQ), estimated metrics (backlinks, referring domains), and why it ranks.
Identify Ranking Patterns
Analyze common characteristics across top 5 results: word count, domain authority, backlinks, content freshness, HTTPS, mobile optimization. Document content format distribution, domain type distribution, and key success factors.
Analyze SERP Features
For each present SERP feature: analyze the current holder, content format, and strategy to win. Cover Featured Snippet (type, content, winning strategy), PAA (questions, current answers, optimization approach), and AI Overview (sources cited, content patterns, citation strategy).
Determine Search Intent
Confirm primary intent from SERP composition. Document evidence, intent breakdown percentages, and content format implications (format, tone, CTA).
Calculate True Difficulty
Score overall difficulty (1-100) based on: top 10 domain authority, page authority, backlinks required, content quality bar, and SERP stability. Provide realistic assessments for new, growing, and established sites, plus easier alternatives.
Generate Recommendations
Produce a summary with: Key Findings, Content Requirements to Rank (minimum requirements + differentiators), SERP Feature Strategy, Recommended Content Outline, and Next Steps.
Reference: See references/analysis-templates.md for detailed templates for each step.
Reference: See references/example-report.md for a complete example analyzing the SERP for "how to start a podcast".
Compare SERPs for [keyword 1], [keyword 2], [keyword 3]
How has the SERP for [keyword] changed over time?
Compare SERP for [keyword] in [location 1] vs [location 2]
Analyze mobile vs desktop SERP differences for [keyword]
After delivering findings to the user, ask:
"Save these results for future sessions?"
If yes, write a dated summary to memory/research/serp-analysis/YYYY-MM-DD-<topic>.md containing:
If any findings should influence ongoing strategy, recommend promoting key conclusions to memory/hot-cache.md.
Install the full suite: See README for one-command install of all 20 skills.