Skills Agentes

Seo Geo

Optimiza contenido para AI Overviews, ChatGPT, Perplexity y otras búsquedas con IA. Analiza señales de menciones de marca, accesibilidad para crawlers de IA, cumplimiento de llms.txt y puntuación de citabilidad a nivel de pasaje.

Estrellas
14.5k

en todo el repo

Actividad
61

0–100, la ruta de este skill

Actualizado
hace 29 días

último commit aquí

Commits
6

últimos 90 días

Contexto
3.7k tok

117 tok en reposo

Paquete
4 archivos

24 KB

Instalar

Funciona con cualquier agente que lea SKILL.md

npx -y skills add AgriciDaniel/claude-seo --skill seo-geo --agent claude-code

Se instala solo en este repositorio.

Qué hace

  • Puntúa 5 criterios GEO: citabilidad de pasajes (25%), legibilidad estructural (20%), contenido multimodal (15%), señales de autoridad/marca (20%) y accesibilidad técnica para crawlers de IA (20%)
  • Revisa qué crawlers de IA (GPTBot, ClaudeBot, PerplexityBot, etc.) están permitidos o bloqueados en robots.txt
  • Reporta la presencia de llms.txt pero sin asignarle peso de ranking, porque Google confirma que lo ignora
  • Encuadra los hallazgos de GEO como fundamentos de SEO clásico aplicados a superficies de búsqueda con IA, no como una disciplina aparte

Úsalo cuando

  • El usuario pide 'AI Overviews', 'SGE', 'GEO', 'AI search', 'Perplexity' o 'AI citations'

No lo uses cuando

    Qué lo activa

    Di cualquiera de estas frases y el agente debería cargar este skill.

    • Optimiza esta página para aparecer en AI Overviews
    • Revisa si mis crawlers de IA están bloqueados

    SKILL.md

    En inglés

    AI Search / GEO Optimization (May 2026)

    Primary Source: Google's AI Optimization Guide

    Google's official position, published under Search Central docs:

    "Optimizing for generative AI search is still SEO from Google's perspective. AEO and GEO are rebranded labels for the same work."

    Read references/google-ai-optimization-guide.md for the full synthesis, myth-busting list (llms.txt, chunking, AI-rephrasing, mention-farming, all rejected by Google as ineffective), and the Who/How/Why test for content quality.

    Audits should frame GEO findings as SEO fundamentals applied to AI-search surfaces, not as a separate optimization discipline. When community recommendations contradict Google's primary source, defer to Google and note the contradiction in the report.

    Key Statistics

    Metric Value Source
    AI Overviews reach 2.5 billion+ monthly active users, reported from Google I/O 2026 keynote coverage; not confirmed on a Google-owned source; 200+ countries Third-party I/O reporting
    AI Overviews query coverage ~50% of queries (third-party measurement; varies by country) Industry data
    AI Mode monthly users 1B+, reported from Google I/O 2026 keynote coverage; not confirmed on a Google-owned source Third-party I/O reporting
    AI Mode model custom version of Gemini 2.5 Google
    AI-referred sessions growth 527% (Jan-May 2025) SparkToro
    ChatGPT weekly active users 900 million OpenAI
    Perplexity monthly queries 500+ million Perplexity

    Critical Insight: Brand Mentions > Backlinks

    Brand mentions correlate 3x more strongly with AI visibility than backlinks. (Ahrefs December 2025 study of 75,000 brands)

    Signal Correlation with AI Citations
    YouTube mentions ~0.737 (strongest)
    Reddit mentions High
    Wikipedia presence High
    LinkedIn presence Moderate
    Domain Rating (backlinks) ~0.266 (weak)

    Only 11% of domains are cited by both ChatGPT and Google AI Overviews for the same query, so platform-specific optimization is essential.


    GEO Analysis Criteria (Updated)

    1. Citability Score (25%)

    Optimal passage length: 134-167 words for AI citation. And ~44% of AI citations come from the first 30% of a page (SE Ranking study), front-load your most citable, self-contained answer rather than burying it below the fold.

    Strong signals:

    • Clear, quotable sentences with specific facts/statistics
    • Self-contained answer blocks (can be extracted without context)
    • Direct answer in first 40-60 words of section
    • Claims attributed with specific sources
    • Definitions following "X is..." or "X refers to..." patterns
    • Unique data points not found elsewhere

    Weak signals:

    • Vague, general statements
    • Opinion without evidence
    • Buried conclusions
    • No specific data points

    2. Structural Readability (20%)

    92% of AI Overview citations come from top-10 ranking pages, but 47% come from pages ranking below position 5, demonstrating different selection logic.

    Strong signals:

    • Clean H1->H2->H3 heading hierarchy
    • Question-based headings (matches query patterns)
    • Short paragraphs (2-4 sentences)
    • Tables for comparative data
    • Ordered/unordered lists for step-by-step or multi-item content
    • FAQ sections with clear Q&A format

    Weak signals:

    • Wall of text with no structure
    • Inconsistent heading hierarchy
    • No lists or tables
    • Information buried in paragraphs

    3. Multi-Modal Content (15%)

    Content with multi-modal elements sees 156% higher selection rates.

    Check for:

    • Text + relevant images
    • Video content (embedded or linked)
    • Infographics and charts
    • Interactive elements (calculators, tools)
    • Structured data supporting media

    4. Authority & Brand Signals (20%)

    Strong signals:

    • Author byline with credentials
    • Publication date and last-updated date
    • Recency, content under 3 months old is ~3x more likely to be cited in AI answers; pages left stale 6+ months lose citation eligibility (SE Ranking, 1.3M-citation study). A scheduled refresh program is one of the highest-leverage GEO plays.
    • Citations to primary sources (studies, official docs, data)
    • Organization credentials and affiliations
    • Expert quotes with attribution
    • Entity presence in Wikipedia, Wikidata
    • Mentions on Reddit, YouTube, LinkedIn

    Weak signals:

    • Anonymous authorship
    • No dates
    • No sources cited
    • No brand presence across platforms

    5. Technical Accessibility (20%)

    AI crawlers do NOT execute JavaScript. Server-side rendering is critical.

    Check for:

    • Server-side rendering (SSR) vs client-only content
    • AI crawler access in robots.txt
    • llms.txt file presence and configuration
    • RSL 1.0 licensing terms

    AI Crawler Detection

    Check robots.txt for these AI crawlers:

    Crawler Owner Purpose Obeys robots.txt?
    GPTBot OpenAI ChatGPT web search yes
    OAI-SearchBot OpenAI OpenAI search features yes
    ChatGPT-User OpenAI ChatGPT browsing (user-triggered) no (user-triggered)
    ClaudeBot Anthropic Claude web features yes
    PerplexityBot Perplexity Perplexity AI search yes
    CCBot Common Crawl Training data (often blocked) yes
    anthropic-ai Anthropic Claude training yes
    Bytespider ByteDance TikTok/Douyin AI yes
    cohere-ai Cohere Cohere models yes
    Google-Extended Google Gemini/Vertex training & grounding opt-out yes
    Google-CloudVertexBot Google Site-owner-requested Vertex AI Agent crawls yes
    Google-Agent Google Agentic browsing (Project Mariner), acts for a user no (user-triggered)
    Google-NotebookLM Google Fetches individual user-added source URLs no (user-triggered)
    Google Messages Google User-triggered fetch no (user-triggered)

    Recommendation: Allow GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot for AI search visibility. Block CCBot and training crawlers if desired.

    User-triggered fetchers ignore robots.txt by design (Google-Agent, Google-NotebookLM, Google Messages, ChatGPT-User). robots.txt cannot block them, use server-side access controls. Google's canonical crawling/robots reference moved to developers.google.com/crawling (migrated 2025-11-20); IP-range files now live at /crawling/ipranges/ and googlebot.json was renamed common-crawlers.json. Emerging: Web Bot Auth (RFC 9421) lets bots authenticate via a Signature-Agent header + key directory (used by Google-Agent); reverse-DNS verification remains the fallback.


    llms.txt Standard

    Read references/llmstxt-evidence.md for the primary-source evidence (Mueller, Illyes, SE Ranking 300k-domain study, OtterlyAI server-log audit) on why /llms.txt is not currently a citation lever for major AI search systems. claude-seo reports presence but assigns no citation-ranking weight.

    Google now states this explicitly. Google's AI optimization guide (updated 2026-06-29) says you do not need llms.txt / AI-text files for Google Search, including its generative AI features, and that doing so "won't harm (nor help) your visibility or rankings in Google Search, as Google Search ignores them." Mueller separately called the llms.txt discovery use case "a dead end." It's fine to keep for non-Google AI services; never recommend it as a Google ranking/citation lever. Source: developers.google.com/search/docs/fundamentals/ai-optimization-guide

    The emerging llms.txt standard provides AI crawlers with structured content guidance.

    Location: /llms.txt (root of domain)

    Format:

    # Title of site
    > Brief description
    
    ## Main sections
    - [Page title](url): Description
    - [Another page](url): Description
    
    ## Optional: Key facts
    - Fact 1
    - Fact 2
    

    Check for:

    • Presence of /llms.txt
    • Structured content guidance
    • Key page highlights
    • Contact/authority information

    RSL 1.0 (Really Simple Licensing)

    New standard (December 2025) for machine-readable AI licensing terms.

    Backed by: Reddit, Yahoo, Medium, Quora, Cloudflare, Akamai, Creative Commons

    Check for: RSL implementation and appropriate licensing terms.


    Platform-Specific Optimization

    Platform Key Citation Sources Optimization Focus
    Google AI Overviews Strongly ranking-correlated, cites pages that already rank well Traditional SEO + passage optimization
    Google AI Mode (custom version of Gemini 2.5) Weakly ranking-correlated; broader pool (~9 domains cited/query, Ahrefs) Distinct surface: freshness, entity authority, citable passages beyond position 5
    ChatGPT Wikipedia (47.9%), Reddit (11.3%) Entity presence, authoritative sources
    Perplexity Reddit (46.7%), Wikipedia Community validation, discussions
    Bing Copilot Bing index, authoritative sites Bing SEO, IndexNow

    Two Google citation engines, not one. AI Mode and AI Overviews reach the same conclusion ~86% of the time but cite the same URLs only 13.7% of the time (Ahrefs study, 540K query pairs). Treat them as separate surfaces: ranking well in classic Search feeds AI Overviews, but AI Mode draws from a broader pool where freshness and entity authority outweigh raw position. Score both.

    UX is now unified, surfaces still distinct. At Google I/O 2026 (2026-05-19) Google merged AI Overviews and AI Mode into "one seamless AI Search experience" (question → AI Overview → follow-up in AI Mode) with a new intelligent Search box. The experience is one flow, but the two citation engines remain technically distinct (different models/link sets), keep scoring both.

    Citation surfaces & controls in AI Search (2026)

    Google added many AI citation/source surfaces across AI Overviews and AI Mode (May 2026):

    • Preferred Sources, users pick sites that get a "preferred" badge in AI answers; all-languages since 2026-04-30 (>345K sources selected); Google is working toward using it as a ranking signal. Quick win: encourage your audience to add the brand as a Preferred Source.
    • "Highly Cited" badges, earned via original primary reporting that other articles cite.
    • Community Perspectives, elevates Reddit/forum/firsthand content.
    • Inline links, desktop hover Link Previews, and prominent link carousels.

    Controlling AI-feature appearance: there is no AI-specific opt-out file. Appearance in AI Overviews and AI Mode is governed by standard preview/index directives, nosnippet, data-nosnippet, max-snippet, noindex (distinct from the third-party AI-crawler robots controls above). Source: developers.google.com/search/docs/appearance/ai-features

    Search agents (live, not just WebMCP): Google's "Information Agents" run in the background to monitor topics, plus agentic booking/calling for select categories (rolling out to US users, summer 2026), so agent-friendly-page optimization (real interactive elements, accessibility tree, layout stability) now matters for actions, not only citations.


    Output

    Generate GEO-ANALYSIS.md with:

    1. GEO Readiness Score: XX/100
    2. Platform breakdown (Google AIO, ChatGPT, Perplexity scores)
    3. AI Crawler Access Status (which crawlers allowed/blocked)
    4. llms.txt Status (present, missing, recommendations)
    5. Brand Mention Analysis (presence on Wikipedia, Reddit, YouTube, LinkedIn)
    6. Passage-Level Citability (optimal 134-167 word blocks identified)
    7. Server-Side Rendering Check (JavaScript dependency analysis)
    8. Top 5 Highest-Impact Changes
    9. Schema Recommendations (for AI discoverability)
    10. Content Reformatting Suggestions (specific passages to rewrite)

    Quick Wins

    1. Add "What is [topic]?" definition in first 60 words
    2. Create 134-167 word self-contained answer blocks
    3. Add question-based H2/H3 headings
    4. Include specific statistics with sources
    5. Add publication/update dates
    6. Implement Person schema for authors
    7. Allow key AI crawlers in robots.txt

    Medium Effort

    1. Create /llms.txt file (optional: ignored by Google Search; may help other AI crawlers)
    2. Add author bio with credentials + Wikipedia/LinkedIn links
    3. Ensure server-side rendering for key content
    4. Build entity presence on Reddit, YouTube
    5. Add comparison tables with data
    6. Implement FAQ sections (structured, not schema for commercial sites)

    High Impact

    1. Create original research/surveys (unique citability)
    2. Build Wikipedia presence for brand/key people
    3. Establish YouTube channel with content mentions
    4. Implement comprehensive entity linking (sameAs across platforms)
    5. Develop unique tools or calculators

    DataForSEO Integration (Optional)

    If DataForSEO MCP tools are available, use ai_optimization_chat_gpt_scraper to check what ChatGPT web search returns for target queries (real GEO visibility check) and ai_opt_llm_ment_search with ai_opt_llm_ment_top_domains for LLM mention tracking across AI platforms.

    Error Handling

    Scenario Action
    URL unreachable (DNS failure, connection refused) Report the error clearly. Do not guess site content. Suggest the user verify the URL and try again.
    AI crawlers blocked by robots.txt Report exactly which crawlers are blocked and which are allowed. Provide specific robots.txt directives to add for enabling AI search visibility.
    No llms.txt found Note the absence (optional file; Google Search ignores it) and provide a ready-to-use llms.txt template for non-Google AI crawlers.
    No structured data detected Report the gap and provide specific schema recommendations (Article, Organization, Person) for improving AI discoverability.

    FLOW Framework Integration

    For prompt-guided AI content optimization, use /seo flow optimize <url>, FLOW's 21 optimize-stage prompts complement GEO's citability and structure analysis with evidence-led AI prompts.

    Reproducido de AgriciDaniel/claude-seo bajo licencia MIT. Leer esta página en markdown.

    Archivos

    4 archivos en el paquete. Solo se lee SKILL.md al activarse — las referencias se cargan si el skill decide que las necesita.

    Detalles

    Categoría
    SEO y GEO
    Licencia
    MIT
    Recursos incluidos
    referencias
    Código fuente
    Ver SKILL.md

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