Skills Agentes

Serp Analyzer

Analiza los resultados de búsqueda de Google (SERP) para cualquier keyword y produce un content brief para superar a la competencia.

Estrellas
688

en todo el repo

Actividad
25

0–100, la ruta de este skill

Actualizado
hace 7 meses

último commit aquí

Commits
0

últimos 90 días

Contexto
3k tok

74 tok en reposo

Paquete
1 archivo

12 KB

Instalar

Funciona con cualquier agente que lea SKILL.md

npx -y skills add OpenClaudia/openclaudia-skills --skill serp-analyzer --agent claude-code

Se instala solo en este repositorio.

Este skill makes network requests, needs API credentials.

Qué hace

  • Recopila datos del SERP de Google para una keyword usando SemRush, SerpAPI, DataForSEO o búsqueda web
  • Mapea las SERP features presentes (featured snippet, PAA, knowledge panel, etc.) y quién las ocupa
  • Analiza los 10 primeros resultados orgánicos (word count, headings, formato, schema, enlaces)
  • Identifica patrones de contenido comunes y gaps que los competidores no cubren
  • Genera un content brief completo con especificaciones, outline, títulos y estrategia de diferenciación

Úsalo cuando

  • El usuario pide analizar el SERP de una keyword
  • El usuario pregunta 'qué rankea para' o 'quién rankea para' un término
  • Se solicita un análisis competitivo o un content brief para una keyword
  • El usuario pregunta por patrones del contenido que está posicionando

No lo uses cuando

    Qué lo activa

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

    • Analiza el SERP para 'mejores herramientas de SEO'
    • ¿Qué está rankeando para 'crm para pymes'?
    • Hazme un content brief para la keyword 'marketing de contenidos'
    • Análisis competitivo para 'software de facturación'

    SKILL.md

    En inglés

    SERP Analyzer Skill

    You are an expert SERP analyst. Given a target keyword, analyze what currently ranks in Google, identify content patterns, and produce an actionable content brief for outranking the competition.

    Prerequisites

    Optional API keys for enriched data (the skill can work without any of them using web search):

    • SEMRUSH_API_KEY - for keyword and organic results data
    • SERPAPI_API_KEY - for real-time Google SERP data including SERP features
    • DATAFORSEO_LOGIN and DATAFORSEO_PASSWORD - for advanced SERP data

    Analysis Process

    Step 1: Collect SERP Data

    Use multiple data sources to build a complete SERP picture:

    Method A: SemRush API (if available)

    # Get organic results for keyword
    https://api.semrush.com/?type=phrase_organic&key={KEY}&phrase={keyword}&database=us&export_columns=Dn,Ur,Fk,Fp&display_limit=20
    

    Columns: Dn=Domain, Ur=URL, Fk=SERP Features, Fp=Position

    Method B: Web Search (always do this) Use the WebSearch tool to search for the exact keyword. This gives you real-time SERP data.

    Method C: Fetch top results Use WebFetch on the top 5-10 ranking URLs to analyze actual content.

    Method D: SerpAPI (if SERPAPI_API_KEY available)

    Real-time Google SERP data with structured SERP features:

    # Real-time Google SERP data via SerpAPI
    curl -s "https://serpapi.com/search.json?q={keyword}&api_key=${SERPAPI_API_KEY}&num=20&gl=us&hl=en"
    

    The JSON response includes:

    • organic_results - Array of organic listings with position, title, link, snippet, displayed_link
    • related_questions - People Also Ask questions with question, snippet, title, link
    • knowledge_graph - Knowledge panel data with title, description, entity_type, and attributes
    • shopping_results - Product listings (if present) with title, price, link, source
    • local_results - Local Pack listings (if present) with title, address, rating, reviews
    • inline_images - Image pack results
    • answer_box - Featured snippet content with type (paragraph, list, table), snippet, title
    • related_searches - Related search queries

    Parse example:

    # Extract organic results
    curl -s "https://serpapi.com/search.json?q={keyword}&api_key=${SERPAPI_API_KEY}&num=20&gl=us&hl=en" | \
      jq '.organic_results[] | {position, title, link, snippet}'
    
    # Extract People Also Ask questions
    curl -s "https://serpapi.com/search.json?q={keyword}&api_key=${SERPAPI_API_KEY}&num=20&gl=us&hl=en" | \
      jq '.related_questions[] | {question, snippet}'
    
    # Check for knowledge graph
    curl -s "https://serpapi.com/search.json?q={keyword}&api_key=${SERPAPI_API_KEY}&num=20&gl=us&hl=en" | \
      jq '.knowledge_graph | {title, description, entity_type}'
    

    SerpAPI is especially useful for mapping SERP features in Step 2, as it returns structured data for every feature type.

    Method E: DataForSEO (if DATAFORSEO_LOGIN and DATAFORSEO_PASSWORD available)

    Advanced SERP data with detailed item types and ranking metrics:

    # DataForSEO SERP API
    curl -s -X POST "https://api.dataforseo.com/v3/serp/google/organic/live/advanced" \
      -H "Authorization: Basic $(echo -n '${DATAFORSEO_LOGIN}:${DATAFORSEO_PASSWORD}' | base64)" \
      -H "Content-Type: application/json" \
      -d '[{"keyword": "{keyword}", "location_code": 2840, "language_code": "en"}]'
    

    The response provides:

    • result[0].items - Array of all SERP items, each with a type field:
      • "organic" - Standard organic results with url, title, description, rank_group, rank_absolute
      • "featured_snippet" - Featured snippet with description, url, type (paragraph/list/table)
      • "people_also_ask" - PAA questions with items[].title (the questions)
      • "knowledge_graph" - Knowledge panel data
      • "local_pack" - Local results
      • "shopping" - Shopping results
      • "video" - Video carousel items
      • "images" - Image pack
      • "related_searches" - Related search suggestions
    • result[0].item_types - Array listing which SERP feature types are present (useful for Step 2 feature mapping)
    • result[0].se_results_count - Total search results count

    Location codes: 2840 = US, 2826 = UK, 2124 = Canada, 2036 = Australia. Change location_code for geo-targeted analysis.

    Step 2: Map SERP Features

    Document every SERP feature present for this keyword:

    Feature Present? Who owns it? Can you win it?
    Featured Snippet Yes/No {domain} {assessment}
    People Also Ask Yes/No {list questions} -
    Knowledge Panel Yes/No {entity} -
    Image Pack Yes/No {position in SERP} {assessment}
    Video Carousel Yes/No {platforms} {assessment}
    Local Pack Yes/No - {assessment}
    Shopping Results Yes/No - {assessment}
    News Results Yes/No {sources} {assessment}
    Sitelinks Yes/No {domain} -
    Reviews/Stars Yes/No {domains} {assessment}
    FAQ Rich Results Yes/No {domains} {assessment}
    Breadcrumbs Yes/No {domains} -

    SERP Intent Signal Analysis:

    • Mostly blog posts/guides = Informational intent
    • Mostly product/service pages = Transactional intent
    • Mix of reviews + product pages = Commercial investigation
    • Brand homepage + login pages = Navigational intent
    • Featured snippet present = Strong informational component

    Step 3: Analyze Top 10 Results

    For each of the top 10 organic results, fetch and analyze:

    Factor What to measure
    URL Full URL
    Domain Domain authority/reputation
    Title tag Exact title, length, keyword placement
    Meta description Exact description, length, call-to-action
    Content type Blog post, landing page, tool, directory, video, etc.
    Word count Total content length
    Heading structure H1, number of H2s/H3s, heading keywords
    Content format Listicle, how-to, comparison, guide, definition, etc.
    Visuals Number of images, videos, infographics, tables
    Date Published date, last updated date
    Author Named author, credentials shown
    Unique angle What differentiates this from others
    Internal links Number of internal links
    External links Number of outbound links, sources cited
    Schema markup Types of structured data used
    Reading level Approximate Flesch-Kincaid grade level

    Step 4: Identify Patterns

    After analyzing all top 10 results, find commonalities:

    Content Pattern Analysis:

    ## Content Patterns for "{keyword}"
    
    ### Dominant Content Type: {type}
    {X} of 10 results are {blog posts/landing pages/tools/etc.}
    
    ### Average Metrics:
    - Word count: {average} (range: {min}-{max})
    - Number of headings: {average}
    - Number of images: {average}
    - Number of links (internal): {average}
    - Number of links (external): {average}
    
    ### Common Topics Covered:
    1. {topic} - covered by {X}/10 results
    2. {topic} - covered by {X}/10 results
    3. {topic} - covered by {X}/10 results
    ...
    
    ### Common H2 Headings:
    1. "{heading}" or similar - used by {X}/10
    2. "{heading}" or similar - used by {X}/10
    ...
    
    ### Featured Snippet Format:
    Type: {paragraph/list/table/video}
    Content: {what the snippet shows}
    How to win it: {specific advice}
    

    Step 5: Find Content Gaps

    Identify what the top results are MISSING:

    • Topics mentioned by only 1-2 results (opportunity to be comprehensive)
    • Outdated information (opportunity for freshness)
    • Missing media types (no videos, no infographics, no interactive tools)
    • Missing perspectives (no expert quotes, no data, no case studies)
    • Unanswered "People Also Ask" questions
    • Missing schema markup types
    • Poor user experience (slow, no mobile optimization, intrusive ads)

    Step 6: Analyze Competitive Positioning

    For each top 5 competitor, create a positioning map:

    Competitor 1 ({domain}): {Positioning summary - e.g., "Beginner-friendly, surface-level guide"}
      Strengths: {what they do well}
      Weaknesses: {what they miss or do poorly}
    
    Competitor 2 ({domain}): {Positioning summary}
      Strengths: ...
      Weaknesses: ...
    

    Find your differentiation angle:

    • Can you be more comprehensive? (10x content)
    • Can you be more actionable? (templates, tools, checklists)
    • Can you be more current? (latest data, 2025 updates)
    • Can you be more authoritative? (expert interviews, original research)
    • Can you serve a different sub-audience? (beginners vs. advanced)
    • Can you provide a unique format? (interactive tool vs. blog post)

    Step 7: Generate Content Brief

    Produce a complete content brief based on the analysis:

    # Content Brief: {Target Keyword}
    
    ## Target Keyword
    - **Primary:** {keyword} (Volume: {vol}, KD: {kd})
    - **Secondary:** {keyword2}, {keyword3}, {keyword4}
    - **Long-tail:** {keyword5}, {keyword6}
    
    ## Search Intent
    **Primary intent:** {Informational/Commercial/Transactional}
    **User goal:** {What the searcher wants to accomplish}
    **Stage in funnel:** {Awareness/Consideration/Decision}
    
    ## Content Specifications
    
    | Spec | Recommendation | Reasoning |
    |------|---------------|-----------|
    | Content type | {blog/landing/tool} | {X}/10 results are this type |
    | Word count | {target} words | Top 3 average {avg}, aim for {target} |
    | Format | {listicle/how-to/guide} | Dominant format in SERP |
    | Reading level | Grade {X} | Match audience expectation |
    | Visuals | {X} images, {X} custom graphics | Top results average {Y} |
    | Videos | {Yes/No - embed or create} | {Reasoning} |
    
    ## Title Tag Recommendations
    Write 3 options following these patterns from top results:
    1. "{Title option 1}" ({length} chars)
    2. "{Title option 2}" ({length} chars)
    3. "{Title option 3}" ({length} chars)
    
    ## Meta Description Recommendations
    1. "{Meta option 1}" ({length} chars)
    2. "{Meta option 2}" ({length} chars)
    
    ## Recommended Outline
    
    ### H1: {Heading}
    
    ### H2: {Section 1 - from pattern analysis}
    - Key points to cover: {points}
    - Data/examples needed: {specifics}
    
    ### H2: {Section 2}
    - Key points: ...
    
    ### H2: {Section 3}
    ...
    
    ### H2: FAQ
    - {Question from People Also Ask}
    - {Question from People Also Ask}
    - {Question from gap analysis}
    
    ## Content Gaps to Exploit
    1. **{Gap}** - Only {X}/10 competitors cover this. Include {specific content}.
    2. **{Gap}** - No competitors have {data/tool/visual}. Create {specific asset}.
    3. **{Gap}** - Top results are outdated on {topic}. Include {current data}.
    
    ## Schema Markup to Include
    - {Type}: {Brief description of properties}
    - {Type}: {Brief description}
    
    ## Internal Linking Targets
    - Link TO this page from: {related pages on your site}
    - Link FROM this page to: {related pages on your site}
    
    ## Differentiation Strategy
    {2-3 sentences on how this content will stand out from current SERP}
    

    Output Format

    Always present:

    1. SERP Overview - Feature map and intent analysis
    2. Top 10 Analysis Table - Key metrics for each result
    3. Pattern Summary - What the SERP rewards
    4. Content Gaps - Opportunities to differentiate
    5. Content Brief - Complete brief ready for a writer

    Notes

    • If you cannot fetch a URL (paywall, auth, blocking), note it and work with available data.
    • Always note the date of analysis. SERPs change; this is a snapshot.
    • For local keywords, note if the Local Pack dominates (this changes the strategy significantly).
    • If the SERP shows extreme domain authority concentration (all DR 90+ sites), flag this as a difficulty indicator regardless of KD score.
    • For "Your Money or Your Life" (YMYL) topics (health, finance, legal), note the elevated E-E-A-T requirements.

    Reproducido de OpenClaudia/openclaudia-skills bajo licencia MIT. Leer esta página en markdown.

    Archivos

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

    Antes de instalar

    Funciona sin claves API usando búsqueda web, pero puede enriquecerse con SEMRUSH_API_KEY, SERPAPI_API_KEY o DATAFORSEO_LOGIN/DATAFORSEO_PASSWORD.

    Necesita en el PATH:curl

    Variables de entorno:DATAFORSEO_LOGINDATAFORSEO_PASSWORDSERPAPI_API_KEY

    Detalles

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

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