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Ai Search Optimization

dirnbauer/webconsulting-skills

  • 247 installs
  • 33 repo stars
  • Updated July 27, 2026
  • dirnbauer/webconsulting-skills

Optimize site content and structure so ChatGPT, Perplexity, Claude, and Google AI Overviews cite your pages in generative and AI-assisted search answers.

About

ai-search-optimization from dirnbauer/webconsulting-skills helps teams improve generative-engine and AI-overview visibility through citation-oriented content, entity structure, and technical signals beyond classic SEO.

  • AEO and GEO copy patterns
  • Entity and citation mapping
  • Structured answer blocks
  • llms.txt and AI crawler signals
  • Competitive AI visibility gaps

Ai Search Optimization by the numbers

  • 247 all-time installs (skills.sh)
  • Ranked #902 of 1,879 Marketing & SEO skills by installs in the Skillselion catalog
  • Data as of Jul 29, 2026 (Skillselion catalog sync)
npx skills add https://github.com/dirnbauer/webconsulting-skills --skill ai-search-optimization

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Installs247
repo stars★ 33
Last updatedJuly 27, 2026
Repositorydirnbauer/webconsulting-skills ↗

What it does

Optimize site content and structure so ChatGPT, Perplexity, Claude, and Google AI Overviews cite your pages in generative and AI-assisted search answers.

Files

SKILL.mdMarkdownGitHub ↗

AI Search Optimization (AEO & GEO)

Source: https://github.com/dirnbauer/webconsulting-skills
Scope: Optimizing content for AI-powered search engines and answer engines
This skill covers strategies for visibility in ChatGPT, Perplexity, Google AI Overviews, Microsoft Copilot, and other generative AI platforms.

1. Understanding AEO & GEO

What is AEO (Answer Engine Optimization)?

Answer Engine Optimization focuses on structuring content to provide direct, concise answers to user queries through AI-powered platforms. Unlike traditional SEO which aims for link clicks, AEO optimizes for being cited as the answer source.

Target platforms:

  • Google AI Overviews (formerly SGE)
  • Perplexity AI
  • ChatGPT Search
  • Microsoft Copilot Search
  • Voice assistants (Siri, Alexa, Google Assistant)

What is GEO (Generative Engine Optimization)?

Generative Engine Optimization is the broader discipline of enhancing content visibility within AI-generated search results. It targets generative engines that synthesize answers from multiple sources rather than presenting traditional link lists.

Key differences from traditional SEO:

AspectTraditional SEOAEO/GEO
GoalRank in SERPsBe cited in AI answers
User behaviorClick through to siteGet answer directly
Content formatKeyword-optimized pagesStructured, citable content
Success metricClick-through rateCitation frequency
Query typeShort keywordsConversational, long-tail

The AI Search Landscape (2025-2026)

  • Google AI Overviews: 2B+ monthly users across 200 countries (TechCrunch)
  • Google AI Mode: 100M+ monthly users in US and India
  • ChatGPT Search: Real-time web search with citations
  • Perplexity AI: Real-time citation engine, emphasis on freshness
  • Microsoft Copilot Search: Bing integration with generative AI
  • Zero-click searches: About 60% of global searches end without a click (neotype.ai)

2. Content Structure for AI Readability

Semantic HTML Structure

AI systems extract information more effectively from well-structured content:

<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <title>Descriptive, Question-Answering Title</title>
</head>
<body>
    <article>
        <header>
            <h1>Primary Topic as Question or Clear Statement</h1>
            <p class="summary">Direct 2-3 sentence answer to the main question.</p>
        </header>
        
        <main>
            <section>
                <h2>Subtopic Heading</h2>
                <p>Detailed explanation with facts and data.</p>
                
                <ul>
                    <li>Key point 1 with specific information</li>
                    <li>Key point 2 with verifiable data</li>
                    <li>Key point 3 with actionable insight</li>
                </ul>
            </section>
        </main>
        
        <aside>
            <h3>Quick Facts</h3>
            <dl>
                <dt>Term</dt>
                <dd>Definition</dd>
            </dl>
        </aside>
    </article>
</body>
</html>

Heading Hierarchy Best Practices

# H1: Main Topic (contains primary question/keyword)
   └── ## H2: Major subtopic
          └── ### H3: Specific aspect
                 └── #### H4: Details (use sparingly)

Rules:

  • Single H1 per page
  • H1 should answer "What is this page about?"
  • Use question-format headings when appropriate
  • Include target keywords naturally

The Inverted Pyramid Pattern

Structure content for AI extraction:

┌─────────────────────────────────────┐
│     DIRECT ANSWER (First 1-2       │ ← AI extracts this
│     sentences answer the query)     │
├─────────────────────────────────────┤
│     KEY FACTS & CONTEXT            │ ← Supporting evidence
│     (Bullet points, data, quotes)   │
├─────────────────────────────────────┤
│     DETAILED EXPLANATION           │ ← Comprehensive coverage
│     (Background, methodology,       │
│      examples, case studies)        │
├─────────────────────────────────────┤
│     RELATED TOPICS                 │ ← Topic authority signals
│     (Links to related content)      │
└─────────────────────────────────────┘

Lists and Tables for Extraction

AI engines prefer structured data formats:

<!-- Comparison Table -->
<table>
    <caption>Feature Comparison: Product A vs Product B</caption>
    <thead>
        <tr>
            <th>Feature</th>
            <th>Product A</th>
            <th>Product B</th>
        </tr>
    </thead>
    <tbody>
        <tr>
            <td>Price</td>
            <td>$99/month</td>
            <td>$149/month</td>
        </tr>
        <!-- More rows -->
    </tbody>
</table>

<!-- Definition List for Terms -->
<dl>
    <dt>AEO</dt>
    <dd>Answer Engine Optimization - optimizing content for direct answers</dd>
    
    <dt>GEO</dt>
    <dd>Generative Engine Optimization - visibility in AI-generated results</dd>
</dl>

<!-- Step-by-Step Process -->
<ol>
    <li>Step one with clear action</li>
    <li>Step two with measurable outcome</li>
    <li>Step three with verification method</li>
</ol>

3. Schema Markup for AI Understanding

Essential Schema Types

Research shows structured data significantly improves AI search visibility:

  • Pages with schema are up to 40% more likely to appear in Google AI Overviews (zarkx.com)
  • Organization schema: 2.8x increase in citation frequency
  • FAQPage schema: 2.5x rise in answer inclusion
  • Article schema: 2.2x boost in content citations
  • Sites with 15+ schema types see 2.4x higher citation rates (surgeboom.com)
FAQPage Schema
{
    "@context": "https://schema.org",
    "@type": "FAQPage",
    "mainEntity": [
        {
            "@type": "Question",
            "name": "What is Answer Engine Optimization?",
            "acceptedAnswer": {
                "@type": "Answer",
                "text": "Answer Engine Optimization (AEO) is a strategic approach to structuring content so AI platforms like ChatGPT, Perplexity, and Google AI Overviews can easily extract and cite it as direct answers to user queries."
            }
        },
        {
            "@type": "Question",
            "name": "How is AEO different from SEO?",
            "acceptedAnswer": {
                "@type": "Answer",
                "text": "While SEO focuses on ranking in traditional search results for clicks, AEO optimizes content to be cited directly in AI-generated answers, often resulting in zero-click interactions where users get information without visiting the source."
            }
        }
    ]
}
HowTo Schema
{
    "@context": "https://schema.org",
    "@type": "HowTo",
    "name": "How to Optimize Content for AI Search",
    "description": "Step-by-step guide to improving visibility in AI-powered search engines",
    "totalTime": "PT30M",
    "step": [
        {
            "@type": "HowToStep",
            "name": "Structure Content Semantically",
            "text": "Use proper HTML5 semantic elements like article, section, and aside",
            "position": 1
        },
        {
            "@type": "HowToStep",
            "name": "Implement Schema Markup",
            "text": "Add FAQPage, HowTo, and Article schema to your pages",
            "position": 2
        },
        {
            "@type": "HowToStep",
            "name": "Optimize for Conversational Queries",
            "text": "Write content that answers natural language questions",
            "position": 3
        }
    ]
}
Article Schema with Author
{
    "@context": "https://schema.org",
    "@type": "Article",
    "headline": "Complete Guide to AI Search Optimization",
    "description": "Learn how to optimize content for ChatGPT, Perplexity, and Google AI Overviews",
    "datePublished": "2025-01-15",
    "dateModified": "2025-01-15",
    "author": {
        "@type": "Person",
        "name": "Expert Name",
        "url": "https://example.com/about/expert-name",
        "jobTitle": "SEO Specialist",
        "sameAs": [
            "https://linkedin.com/in/expertname",
            "https://twitter.com/expertname"
        ]
    },
    "publisher": {
        "@type": "Organization",
        "name": "Company Name",
        "logo": {
            "@type": "ImageObject",
            "url": "https://example.com/logo.png"
        }
    }
}
Organization Schema
{
    "@context": "https://schema.org",
    "@type": "Organization",
    "name": "Company Name",
    "url": "https://example.com",
    "logo": "https://example.com/logo.png",
    "description": "Brief description of what the organization does",
    "foundingDate": "2010",
    "sameAs": [
        "https://www.linkedin.com/company/companyname",
        "https://twitter.com/companyname",
        "https://github.com/companyname"
    ],
    "contactPoint": {
        "@type": "ContactPoint",
        "telephone": "+1-555-123-4567",
        "contactType": "customer service",
        "availableLanguage": ["English", "German"]
    }
}

Detailed Reference

Read the full guide when the task needs detailed examples, long templates, troubleshooting matrices, appendices, or sections not included above. Keep this file unloaded for narrow tasks so the skill follows progressive disclosure.

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