ClawNetClawNet

AI SEO Optimization Skill

Modern SEO for the AI-powered search era. Covers entity-based optimization, AI citation building, multi-platform visibility, E-E-A-T implementation, and technical SEO for 2025 and beyond.

AI SEO Audit Process

Run this sequence for any SEO analysis task:

  1. Entity Analysis — Check brand recognition across AI platforms (Google Knowledge Graph, Wikidata, Wikipedia)
  2. Content Structure — Assess AI-readability: clear headings, tables, FAQs, direct answers at top
  3. Schema Coverage — Audit structured data completeness (Organization, Article, FAQ, HowTo, Product)
  4. Citation Tracking — Check visibility in AI responses (Google AI Overviews, ChatGPT, Perplexity)
  5. Technical Health — Core Web Vitals, mobile-first, robots.txt, XML sitemaps

Entity-Based SEO

Brand Entity Building:

  • Establish unique, consistent brand name and description across all platforms
  • Create and verify Wikipedia/Wikidata entries where notability exists
  • Build social profile network (Twitter/X, LinkedIn, GitHub, Crunchbase) with consistent brand data
  • Implement sameAs schema markup linking all brand entity sources

Schema Priority Order:

{
  "@context": "https://schema.org",
  "@graph": [
    { "@type": "Organization", "name": "...", "sameAs": ["..."] },
    { "@type": "WebSite", "publisher": {"@id": "#organization"} },
    { "@type": "Article", "author": {"@type": "Person"}, "dateModified": "2025-01-01" }
  ]
}

AI Citation Optimization

Content structure for AI platforms to cite:

  1. Quick Answer at top — Direct 2-3 sentence response to the main question before any detail
  2. Structured sections — Clear H2/H3 hierarchy with descriptive headings
  3. Data tables — Comparisons and specifications in table format (AI systems love to pull these)
  4. FAQ sections — Q&A format at the bottom of long-form content
  5. Authoritative sources — External citations, author credentials, publication dates

Platform-Specific Requirements:

Platform Key Factor Optimization
Google AI Overviews Featured snippet presence Direct answer + FAQ schema
ChatGPT Training data coverage + recency Authoritative content + consistent publishing
Perplexity Source credibility + freshness High-quality external links + recent dates
Gemini Technical accuracy + depth Expert author bios + citations
Bing Chat Microsoft ecosystem Bing Webmaster Tools + IndexNow

Content Optimization Workflow

  1. Query Analysis — Identify natural language and long-tail variations of the target topic
  2. Topic Clustering — Map all subtopics and create comprehensive coverage across linked pages
  3. Internal Linking — Build semantic relationships between related content
  4. Format Variety — Use tables, numbered lists, Q&As, and comparison charts (all AI-parseable formats)
  5. Human Voice — Add first-person experience, original data, and brand-specific perspective

E-E-A-T Implementation

Experience: Demonstrate first-hand knowledge — case studies, original research, specific examples from actual use

Expertise: Author credentials in bio, bylines on all content, topic specialization signals

Authoritativeness: Industry citations, press mentions, guest contributions to authority publications

Trustworthiness: Transparent sourcing, fact-checking processes, clear contact information, privacy policy

Notability: Brand mentions across independent sources, recognition from authorities in the field

Technical SEO

Core Web Vitals targets:

  • LCP (Largest Contentful Paint): < 2.5s
  • INP (Interaction to Next Paint): < 200ms
  • CLS (Cumulative Layout Shift): < 0.1

Crawl and index health:

  • XML sitemap with priority and lastmod signals
  • robots.txt with explicit AI crawler rules (note: blocking AI crawlers affects training inclusion)
  • Canonical tags to prevent duplicate content
  • Hreflang for international sites

AI Crawler Management (robots.txt):

# Allow all crawlers including AI
User-agent: *
Allow: /

# Or selectively block AI training crawlers
User-agent: GPTBot
Disallow: /

User-agent: CCBot
Disallow: /

Key AI SEO Metrics

Metric What It Measures
Citation Share % of AI responses mentioning brand for target queries
Entity Score Knowledge graph completeness (Wikidata + schema coverage)
AI Visibility Index Cross-platform presence in AI-generated responses
Query Coverage % of natural language query variants ranking
Featured Snippet Share % of target queries where content appears in featured snippet

Reference Files

For detailed implementation guidance, consult:

  • Invoke Skill(marketing-skills:seo-audit) for full SEO audit workflow
  • Invoke Skill(marketing-skills:schema-markup) for structured data implementation
  • Invoke Skill(marketing-skills:programmatic-seo) for programmatic SEO strategies