AI Search Optimization (AEO & GEO)

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.

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:

Aspect Traditional SEO AEO/GEO

Goal Rank in SERPs Be cited in AI answers

User behavior Click through to site Get answer directly

Content format Keyword-optimized pages Structured, citable content

Success metric Click-through rate Citation frequency

Query type Short keywords Conversational, 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)

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>

    &#x3C;main>
        &#x3C;section>
            &#x3C;h2>Subtopic Heading&#x3C;/h2>
            &#x3C;p>Detailed explanation with facts and data.&#x3C;/p>
            
            &#x3C;ul>
                &#x3C;li>Key point 1 with specific information&#x3C;/li>
                &#x3C;li>Key point 2 with verifiable data&#x3C;/li>
                &#x3C;li>Key point 3 with actionable insight&#x3C;/li>
            &#x3C;/ul>
        &#x3C;/section>
    &#x3C;/main>
    
    &#x3C;aside>
        &#x3C;h3>Quick Facts&#x3C;/h3>
        &#x3C;dl>
            &#x3C;dt>Term&#x3C;/dt>
            &#x3C;dd>Definition&#x3C;/dd>
        &#x3C;/dl>
    &#x3C;/aside>
&#x3C;/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:

<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>  </tbody> </table>

<dl> <dt>AEO</dt> <dd>Answer Engine Optimization - optimizing content for direct answers</dd>

&#x3C;dt>GEO&#x3C;/dt>
&#x3C;dd>Generative Engine Optimization - visibility in AI-generated results&#x3C;/dd>

</dl>

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

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"] } }

E-E-A-T Signals for AI Trust

Experience, Expertise, Authoritativeness, Trustworthiness

AI systems prioritize content from credible sources. Implement these signals:

Author Bios

&#x3C;footer class="author-bio">
    &#x3C;img src="/authors/jane-doe.jpg" alt="Jane Doe" />
    &#x3C;div class="author-info">
        &#x3C;h4>About the Author&#x3C;/h4>
        &#x3C;p class="author-name">Jane Doe, PhD&#x3C;/p>
        &#x3C;p class="author-credentials">
            15 years of experience in digital marketing. 
            Former Head of SEO at Fortune 500 company.
            Published in Search Engine Journal, Moz, and Ahrefs Blog.
        &#x3C;/p>
        &#x3C;ul class="author-links">
            &#x3C;li>&#x3C;a href="https://linkedin.com/in/janedoe" rel="author">LinkedIn&#x3C;/a>&#x3C;/li>
            &#x3C;li>&#x3C;a href="https://twitter.com/janedoe" rel="author">Twitter&#x3C;/a>&#x3C;/li>
        &#x3C;/ul>
    &#x3C;/div>
&#x3C;/footer>

</article>

Trust Signals Checklist

Author expertise: Detailed bios with credentials and experience
Citations: Link to reputable sources (studies, official docs, experts)
Contact information: Clear "About Us" and "Contact" pages
HTTPS: Secure connection required
Privacy policy: Transparent data handling
Update dates: Visible "Last updated" timestamps
Original research: Proprietary data, case studies, expert quotes
Reviews/testimonials: Third-party validation where applicable

Building Domain Authority

Earn quality backlinks from reputable industry sites
Get mentioned in authoritative publications
Contribute guest posts to established platforms
Participate in industry forums and communities
Create original research that others cite

Content Freshness Strategy

Update Frequency by Platform

Platform Freshness Preference Recommended Update Cycle

Perplexity AI Very high Every 2-3 days for trending topics

ChatGPT Search High Weekly updates

Google AI Overviews Moderate Monthly refresh

Bing Copilot Moderate Monthly refresh

Content Refresh Protocol

Content Freshness Checklist

Weekly Tasks

Update statistics with latest data
Refresh screenshots and examples
Add new developments or news
Update "Last modified" timestamp

Monthly Tasks

Review and update all factual claims
Add new sections for emerging topics
Update broken links
Refresh expert quotes

Quarterly Tasks

Comprehensive content audit
Competitive analysis
Restructure based on query trends
Update all schema markup

Visible Timestamps

<article> <header> <h1>Article Title</h1> <div class="article-meta"> <time datetime="2025-01-15" itemprop="datePublished"> Published: January 15, 2025 </time> <time datetime="2025-01-15" itemprop="dateModified"> Last Updated: January 15, 2025 </time> </div> </header>  </article>

Robots.txt for AI Crawlers

Allowing AI Bots

To be indexed by AI search engines, explicitly allow their crawlers:

robots.txt - AI Search Optimization

Standard search engines

User-agent: Googlebot Allow: /

User-agent: Bingbot Allow: /

OpenAI (ChatGPT)

User-agent: GPTBot Allow: /

User-agent: ChatGPT-User Allow: /

Perplexity AI

User-agent: PerplexityBot Allow: /

Anthropic (Claude)

User-agent: ClaudeBot Allow: / User-agent: anthropic-ai Allow: /

Google AI (Gemini)

User-agent: Google-Extended Allow: /

Meta AI

User-agent: FacebookBot Allow: /

Common Crawl (used by many AI systems)

User-agent: CCBot Allow: /

Microsoft/Bing AI

User-agent: Applebot Allow: /

Default rule

User-agent: * Allow: / Disallow: /admin/ Disallow: /private/

Sitemap

Sitemap: https://example.com/sitemap.xml

Blocking AI Training While Allowing AI Search (Optional)

Some organizations want to be cited in AI search results but don't want their content used to train AI models. Here's how:

Understanding the difference:

Bot What it does Block =

GPTBot

Crawls for training OpenAI models Your content won't train future GPT versions

ChatGPT-User

Live browsing when users search ChatGPT can't cite you in real-time answers

Google-Extended

Crawls for training Gemini AI Your content won't train Gemini

PerplexityBot

Live search for Perplexity answers Perplexity can't cite you

CCBot

Common Crawl - open training datasets Your content won't be in public AI training data

Example: Block training, allow live search citations:

BLOCK: AI model training (your content won't train future AI)

User-agent: GPTBot Disallow: /

User-agent: Google-Extended Disallow: /

User-agent: CCBot Disallow: /

ALLOW: Real-time AI search (AI can cite you in answers)

User-agent: ChatGPT-User Allow: /

User-agent: PerplexityBot Allow: /

Note: Most businesses focused on AI search visibility should allow all bots (Section 6 above). Only use this approach if you have specific concerns about AI training on your content.

AI Bot Reference

Bot Name Company Purpose

GPTBot OpenAI Training data & ChatGPT browsing

ChatGPT-User OpenAI ChatGPT web browsing

PerplexityBot Perplexity Real-time search & citations

ClaudeBot Anthropic Training & retrieval

anthropic-ai Anthropic Claude AI training

Google-Extended Google Gemini AI training

FacebookBot Meta Meta AI training

CCBot Common Crawl Open dataset for AI training

Conversational Query Optimization

Target Long-Tail, Question-Based Queries

AI search favors natural language:

Traditional keyword: "best project management software"

Conversational queries:

"What is the best project management software for small teams?"
"How do I choose project management software for remote work?"
"Which project management tool has the best free plan?"

Question-Answer Content Pattern

What is [Topic]?

[Topic] is [direct definition in 1-2 sentences].

Key characteristics:

Characteristic 1
Characteristic 2
Characteristic 3

How does [Topic] work?

[Clear explanation of process]

Step-by-step breakdown:

First step
Second step
Third step

Why is [Topic] important?

[2-3 sentences on significance]

Benefits include:

Benefit 1 with specific outcome
Benefit 2 with measurable result
Benefit 3 with real-world application

FAQ Section Template

<section class="faq"> <h2>Frequently Asked Questions</h2>

&#x3C;details>
    &#x3C;summary>What is Answer Engine Optimization?&#x3C;/summary>
    &#x3C;p>Answer Engine Optimization (AEO) is the practice of...&#x3C;/p>
&#x3C;/details>

&#x3C;details>
    &#x3C;summary>How is GEO different from traditional SEO?&#x3C;/summary>
    &#x3C;p>While traditional SEO focuses on...&#x3C;/p>
&#x3C;/details>

&#x3C;details>
    &#x3C;summary>Which AI search platforms should I optimize for?&#x3C;/summary>
    &#x3C;p>The main platforms to consider are...&#x3C;/p>
&#x3C;/details>

</section>

Multimedia Optimization

Image Requirements

Perplexity and other AI engines prefer visual content:

<figure> <img src="/images/ai-search-diagram.webp" alt="Diagram showing how AI search engines process and cite content" width="800" height="450" loading="lazy" /> <figcaption> How AI search engines extract and cite content sources </figcaption> </figure>

Best practices:

Minimum 2 unique, relevant images per article
Descriptive alt text (not keyword stuffing)
WebP format for performance
Include diagrams, infographics, process flows
Add captions with context

Video Integration

<figure class="video-embed"> <iframe src="https://www.youtube.com/embed/VIDEO_ID" title="Detailed explanation of AI Search Optimization" allow="accelerometer; autoplay; clipboard-write; encrypted-media" allowfullscreen ></iframe> <figcaption> Video: Complete guide to optimizing for AI search engines </figcaption> </figure>

Video Schema

{ "@context": "https://schema.org", "@type": "VideoObject", "name": "AI Search Optimization Tutorial", "description": "Learn how to optimize content for ChatGPT, Perplexity, and Google AI", "thumbnailUrl": "https://example.com/video-thumbnail.jpg", "uploadDate": "2025-01-15", "duration": "PT10M30S", "contentUrl": "https://example.com/videos/ai-search-tutorial.mp4" }

Monitoring AI Search Visibility

AI Brand Monitoring Tools

Tool Platforms Monitored Key Features

Semrush AI Visibility ChatGPT, Gemini, Perplexity Free tier, mention tracking

Brand24 ChatGPT, Perplexity, Claude, Gemini Multi-platform analysis

SE Ranking Google AI Overviews, ChatGPT, Gemini Share of voice tracking

Keyword.com Google AI Overviews, ChatGPT, Perplexity Optimization suggestions

BrandBeacon.ai ChatGPT, Perplexity Competitor benchmarking

Sight AI ChatGPT, Claude, Perplexity Sentiment analysis

Key Metrics to Track

Citation frequency: How often your content is cited
Brand mentions: Unprompted mentions in AI responses
Referral traffic: Visits from AI search click-throughs
Share of voice: Your visibility vs competitors
Sentiment: Positive/negative context of mentions

Manual Testing Protocol

Monthly AI Visibility Audit

Test Queries (adapt to your niche)

"What is [your product/service]?"
"Best [your category] in [year]"
"[Your brand] vs [competitor]"
"How to [task your product solves]"
"[Your expertise area] best practices"

Platforms to Test

ChatGPT (chat.openai.com)
Perplexity (perplexity.ai)
Google (check for AI Overviews)
Microsoft Copilot (copilot.microsoft.com)
Claude (claude.ai)

Record for Each Query

Were you cited? (Yes/No)
Citation context (positive/neutral/negative)
Competitors mentioned
Information accuracy
Suggested improvements

AI Search Optimization Checklist

Content Structure

Clear H1 with primary topic/question
Logical heading hierarchy (H1 > H2 > H3)
Direct answer in first 1-2 sentences
Bullet points and numbered lists
Comparison tables where applicable
Definition lists for terminology

Technical Implementation

Semantic HTML5 elements (article, section, aside)
FAQPage schema on Q&A content
HowTo schema on instructional content
Article schema with author info
Organization schema on about pages
robots.txt allows AI crawlers
XML sitemap updated and submitted

Authority Signals

Detailed author bios with credentials
Links to author social profiles
Citations to authoritative sources
Visible publication and update dates
HTTPS enabled
Contact information accessible
Privacy policy present

Content Quality

Original, expert-level content
Factual claims supported by sources
Regular updates (at least monthly)
Addresses conversational queries
Includes relevant images with alt text
Mobile-responsive design

Monitoring

AI visibility monitoring tool configured
Monthly manual query testing
Competitor citation tracking
Referral traffic analysis
Content refresh schedule maintained

Platform-Specific Optimization

Google AI Overviews

Pages with schema are up to 40% more likely to appear in AI Overviews
Focus on featured snippet optimization (still relevant)
Emphasize E-E-A-T signals
Target informational and comparison queries

Perplexity AI

Freshness is critical - update content every 2-3 days for trending topics
Real-time citations from current sources
Prefer authoritative domains
Include unique images and data

ChatGPT Search

Web browsing uses GPTBot and ChatGPT-User
Emphasizes recent, authoritative content
Good at following citations and references
Benefits from clear, structured content

Microsoft Copilot

Built on Bing index
Strong integration with Microsoft ecosystem
Emphasizes factual, well-sourced content
Benefits from Bing Webmaster Tools optimization

Future-Proofing Your AI Search Strategy

Emerging Trends

Multimodal search: AI understanding images, video, audio
Conversational commerce: AI-driven purchase decisions
Personalized AI responses: Context-aware answer customization
Agent-based search: AI agents completing tasks autonomously
Real-time fact-checking: AI validating claims before citation

Adaptation Strategy

Quarterly Review Checklist

AI Platform Updates

Review new AI search features from major platforms
Update robots.txt for new AI bot user agents
Test visibility on new/emerging AI platforms

Content Strategy

Analyze which content types get most citations
Identify gaps in AI coverage vs competitors
Plan new content for underserved queries

Technical Updates

Review schema.org for new relevant types
Update structured data implementation
Test page speed and Core Web Vitals

TYPO3 Implementation Guide

Compatibility: TYPO3 v13.x and v14.x (v14 preferred) All configurations in this section work on both v13 and v14.

This section covers TYPO3-specific implementation of AEO/GEO strategies using TYPO3 extensions, configuration, and best practices.

Installation Mode: Composer vs Classic

⚠️ Composer Mode Highly Recommended

For AI search optimization, Composer-based TYPO3 installations are strongly recommended. All extensions in this guide are available via both Composer (Packagist) and TER (Classic Mode).

Why Composer Mode is Essential for Modern TYPO3

Aspect Composer Mode Classic Mode

Dependency Resolution Automatic with version constraints Manual, no transitive dependencies

Autoloading PSR-4 optimized, production-ready TYPO3 internal, less optimized

Security Separate web root (/public ) All files in web root

Updates Single command: composer update

Manual download/upload per extension

Reproducibility composer.lock ensures identical installs No version locking mechanism

TYPO3 v14 Future Fully supported Requires composer.json in all extensions

Technical Explanation

Composer Mode uses PHP's standard dependency manager to:

Resolve Dependencies Automatically: Extensions like brotkrueml/schema depend on psr/http-message and other packages. Composer resolves the entire dependency tree, ensuring compatible versions are installed.

Generate Optimized Autoloaders: Composer creates a PSR-4 compliant autoloader that loads classes on-demand, improving performance compared to TYPO3's legacy class loading.

Enforce Version Constraints: The composer.json constraint "typo3/cms-core": "^13.4 || ^14.0" guarantees only compatible versions are installed.

Enable Security Isolation: The recommended structure places vendor/ , config/ , and other sensitive directories outside the web-accessible /public folder.

Support Modern Workflows: CI/CD pipelines, automated testing, and deployment tools expect Composer-based projects.

TYPO3 v14 Breaking Change: In TYPO3 v14, even Classic Mode requires every extension to have a valid composer.json with proper type and extension-key definitions. Extensions without this file will not be detected.

// Required composer.json structure for all extensions (v14+) { "name": "vendor/extension-key", "type": "typo3-cms-extension", "extra": { "typo3/cms": { "extension-key": "extension_key" } } }

Extension Compatibility Matrix

Extension TYPO3 v13 TYPO3 v14 PHP Composer TER Purpose

typo3/cms-seo

✓ ✓ 8.2+ ✓ ✓ Core SEO (meta tags, sitemaps, canonicals)

brotkrueml/schema

✓ (v4.x) ✓ (v4.x) 8.2+ ✓ ✓ Schema.org structured data (JSON-LD)

yoast-seo-for-typo3/yoast_seo

✓ ✗ 8.1+ ✓ ✓ Content analysis, readability (v13 only)

clickstorm/cs_seo

✓ (v9.3+) ✓ (v9.3+) 8.2+ ✓ ✓ Extended SEO features, evaluations

13.1 Required Extensions Installation

Composer Mode (Recommended)

Core SEO extension (meta tags, sitemaps, canonicals)

ddev composer require typo3/cms-seo

Schema.org structured data (essential for AI search)

Version constraint ensures v13/v14 compatibility

ddev composer require brotkrueml/schema:"^4.2"

Optional: Extended SEO features (v13/v14 compatible)

ddev composer require clickstorm/cs_seo:"^9.3"

In Composer mode, extensions are auto-activated

Verify installation:

ddev typo3 extension:list | grep -E "seo|schema"

Version Constraints Explained:

{ "require": { "typo3/cms-seo": "^13.4 || ^14.0", "brotkrueml/schema": "^4.2" } }

^4.2 = Any version ≥4.2.0 and <5.0.0 (allows minor/patch updates)
^13.4 || ^14.0 = Supports both TYPO3 v13.4+ and v14.0+

Classic Mode (TER)

Note: Classic Mode is supported but not recommended. TYPO3 v14 requires all extensions to have a valid composer.json even in Classic Mode.

Download from TER:

Install via Extension Manager:

Backend → Admin Tools → Extensions
Click "Upload Extension" or use "Get Extensions" to search TER
Activate each extension after upload

Verify Installation:

Check Admin Tools → Extensions for active status
Clear all caches after activation

13.2 Robots.txt Configuration for AI Bots

Configure robots.txt via TYPO3's static routes to allow AI crawlers:

config/sites/main/config.yaml

routes:

route: robots.txt type: staticText content: |

Standard search engines

User-agent: Googlebot Allow: /

User-agent: Bingbot Allow: /

OpenAI (ChatGPT)

User-agent: GPTBot Allow: /

User-agent: ChatGPT-User Allow: /

Perplexity AI

User-agent: PerplexityBot Allow: /

Anthropic (Claude)

User-agent: ClaudeBot Allow: /

User-agent: anthropic-ai Allow: /

Google AI (Gemini)

User-agent: Google-Extended Allow: /

Meta AI

User-agent: FacebookBot Allow: /

Common Crawl (used by many AI systems)

User-agent: CCBot Allow: /

Default

User-agent: * Allow: / Disallow: /typo3/ Disallow: /typo3conf/ Disallow: /typo3temp/

Sitemap: https://example.com/sitemap.xml

13.3 Schema.org Implementation with EXT:schema

Installation and Setup

ddev composer require brotkrueml/schema:"^4.2" ddev typo3 extension:activate schema

Include the static TypoScript template in your site package.

FAQPage Schema via Fluid ViewHelper

{namespace schema=Brotkrueml\Schema\ViewHelpers}

<schema:type.fAQPage> <f:for each="{faqItems}" as="faq"> <schema:type.question -as="mainEntity" name="{faq.question}"> <schema:type.answer -as="acceptedAnswer" text="{faq.answer}" /> </schema:type.question> </f:for> </schema:type.fAQPage>

Article Schema via Fluid ViewHelper

{namespace schema=Brotkrueml\Schema\ViewHelpers}

<schema:type.article -id="https://example.com/article/{article.uid}" headline="{article.title}" description="{article.teaser}" datePublished="{article.crdate -> f:format.date(format: 'c')}" dateModified="{article.tstamp -> f:format.date(format: 'c')}"

&#x3C;schema:type.person -as="author"

    name="{article.author.name}"
    url="{article.author.profileUrl}"
>
    &#x3C;schema:property -as="sameAs" value="{article.author.linkedIn}" />
    &#x3C;schema:property -as="sameAs" value="{article.author.twitter}" />
&#x3C;/schema:type.person>

&#x3C;schema:type.organization -as="publisher"
    name="{settings.siteName}"
    url="{settings.siteUrl}"
>
    &#x3C;schema:type.imageObject -as="logo" url="{settings.logoUrl}" />
&#x3C;/schema:type.organization>

</schema:type.article>

HowTo Schema via Fluid ViewHelper

{namespace schema=Brotkrueml\Schema\ViewHelpers}

<schema:type.howTo name="How to Optimize Content for AI Search" description="Step-by-step guide to improving visibility in AI-powered search engines"

&#x3C;f:for each="{steps}" as="step" iteration="iter">

    &#x3C;schema:type.howToStep -as="step"
        name="{step.title}"
        text="{step.description}"
        position="{iter.cycle}"
    />
&#x3C;/f:for>

</schema:type.howTo>

Organization Schema via PHP API (PSR-14 Event)

<?php

declare(strict_types=1);

namespace Vendor\SitePackage\EventListener;

use Brotkrueml\Schema\Event\RenderAdditionalTypesEvent; use Brotkrueml\Schema\Type\TypeFactory; use TYPO3\CMS\Core\Attribute\AsEventListener;

#[AsEventListener(identifier: 'site-package/add-organization-schema')] final readonly class AddOrganizationSchema { public function __construct( private TypeFactory $typeFactory, ) {}

public function __invoke(RenderAdditionalTypesEvent $event): void
{
    $organization = $this->typeFactory->create('Organization')
        ->setProperty('name', 'Your Company Name')
        ->setProperty('url', 'https://example.com')
        ->setProperty('logo', 'https://example.com/logo.png')
        ->setProperty('description', 'Brief company description for AI understanding')
        ->setProperty('sameAs', [
            'https://www.linkedin.com/company/yourcompany',
            'https://twitter.com/yourcompany',
            'https://github.com/yourcompany',
        ]);

    $contactPoint = $this->typeFactory->create('ContactPoint')
        ->setProperty('telephone', '+43-1-234567')
        ->setProperty('contactType', 'customer service')
        ->setProperty('availableLanguage', ['German', 'English']);

    $organization->setProperty('contactPoint', $contactPoint);

    $event->addType($organization);
}

}

Dynamic Article Schema via PSR-14 Event

<?php

declare(strict_types=1);

namespace Vendor\SitePackage\EventListener;

use Brotkrueml\Schema\Event\RenderAdditionalTypesEvent; use Brotkrueml\Schema\Type\TypeFactory; use TYPO3\CMS\Core\Attribute\AsEventListener;

#[AsEventListener(identifier: 'site-package/add-article-schema')] final readonly class AddArticleSchema { public function __construct( private TypeFactory $typeFactory, ) {}

public function __invoke(RenderAdditionalTypesEvent $event): void
{
    $request = $event->getRequest();
    $pageInformation = $request->getAttribute('frontend.page.information');
    $page = $pageInformation->getPageRecord();

    // Only add Article schema for specific doktypes (e.g., 1 = standard page)
    if ((int)$page['doktype'] !== 1) {
        return;
    }

    $article = $this->typeFactory->create('Article')
        ->setProperty('headline', $page['title'])
        ->setProperty('description', $page['description'] ?: $page['abstract'])
        ->setProperty('datePublished', date('c', $page['crdate']))
        ->setProperty('dateModified', date('c', $page['tstamp']));

    // Add author if available
    if (!empty($page['author'])) {
        $author = $this->typeFactory->create('Person')
            ->setProperty('name', $page['author']);
        $article->setProperty('author', $author);
    }

    $event->addType($article);
}

}

13.4 Content Freshness with Last Modified Headers

TypoScript Configuration

Expose last modified date in HTTP headers

config { sendCacheHeaders = 1 additionalHeaders { 10 { header = X-Content-Last-Modified value = TEXT value.data = page:SYS_LASTCHANGED value.strftime = %Y-%m-%dT%H:%M:%S%z } } }

Display last updated date in content

lib.lastModified = TEXT lib.lastModified { data = page:SYS_LASTCHANGED strftime = %B %d, %Y wrap = <time datetime="|" itemprop="dateModified">Last updated: |</time> }

Fluid Template for Visible Timestamps

<article itemscope itemtype="https://schema.org/Article"> <header> <h1 itemprop="headline">{page.title}</h1> <div class="article-meta"> <time datetime="{page.crdate -> f:format.date(format: 'c')}" itemprop="datePublished"> Published: <f:format.date format="F j, Y">{page.crdate}</f:format.date> </time> <time datetime="{page.SYS_LASTCHANGED -> f:format.date(format: 'c')}" itemprop="dateModified"> Last Updated: <f:format.date format="F j, Y">{page.SYS_LASTCHANGED}</f:format.date> </time> </div> </header>

&#x3C;!-- Content -->

</article>

13.5 Author Bio Schema for E-E-A-T

TCA Extension for Author Fields

<?php // Configuration/TCA/Overrides/pages.php

use TYPO3\CMS\Core\Utility\ExtensionManagementUtility;

$additionalColumns = [ 'tx_sitepackage_author_name' => [ 'label' => 'Author Name', 'config' => [ 'type' => 'input', 'size' => 50, 'max' => 255, ], ], 'tx_sitepackage_author_title' => [ 'label' => 'Author Title/Credentials', 'config' => [ 'type' => 'input', 'size' => 50, 'max' => 255, ], ], 'tx_sitepackage_author_bio' => [ 'label' => 'Author Bio', 'config' => [ 'type' => 'text', 'rows' => 5, ], ], 'tx_sitepackage_author_linkedin' => [ 'label' => 'Author LinkedIn URL', 'config' => [ 'type' => 'link', 'allowedTypes' => ['url'], ], ], ];

ExtensionManagementUtility::addTCAcolumns('pages', $additionalColumns); ExtensionManagementUtility::addToAllTCAtypes( 'pages', '--div--;Author,tx_sitepackage_author_name,tx_sitepackage_author_title,tx_sitepackage_author_bio,tx_sitepackage_author_linkedin' );

Author Schema PSR-14 Event Listener

<?php

declare(strict_types=1);

namespace Vendor\SitePackage\EventListener;

use Brotkrueml\Schema\Event\RenderAdditionalTypesEvent; use Brotkrueml\Schema\Type\TypeFactory; use TYPO3\CMS\Core\Attribute\AsEventListener;

#[AsEventListener(identifier: 'site-package/add-author-schema')] final readonly class AddAuthorSchema { public function __construct( private TypeFactory $typeFactory, ) {}

public function __invoke(RenderAdditionalTypesEvent $event): void
{
    $request = $event->getRequest();
    $pageInformation = $request->getAttribute('frontend.page.information');
    $page = $pageInformation->getPageRecord();

    if (empty($page['tx_sitepackage_author_name'])) {
        return;
    }

    $author = $this->typeFactory->create('Person')
        ->setProperty('name', $page['tx_sitepackage_author_name'])
        ->setProperty('jobTitle', $page['tx_sitepackage_author_title'] ?? '')
        ->setProperty('description', $page['tx_sitepackage_author_bio'] ?? '');

    if (!empty($page['tx_sitepackage_author_linkedin'])) {
        $author->setProperty('sameAs', [$page['tx_sitepackage_author_linkedin']]);
    }

    $event->addType($author);
}

}

13.6 FAQ Content Element with Schema

Content Block Definition (EXT:content_blocks)

ContentBlocks/ContentElements/faq-accordion/config.yaml

name: vendor/faq-accordion typeName: faq_accordion title: FAQ Accordion description: FAQ with structured data for AI search group: common

fields:

identifier: faq_items type: Collection labelField: question fields:
- identifier: question type: Text required: true
- identifier: answer type: Textarea enableRichtext: true required: true

Fluid Template with Schema

{namespace schema=Brotkrueml\Schema\ViewHelpers}

<section class="faq-accordion"> <schema:type.fAQPage> <f:for each="{data.faq_items}" as="item"> <schema:type.question -as="mainEntity" name="{item.question}"> <schema:type.answer -as="acceptedAnswer"> <schema:property -as="text" value="{item.answer -> f:format.stripTags()}" /> </schema:type.answer> </schema:type.question>

        &#x3C;details class="faq-item">
            &#x3C;summary class="faq-question">{item.question}&#x3C;/summary>
            &#x3C;div class="faq-answer">
                &#x3C;f:format.html>{item.answer}&#x3C;/f:format.html>
            &#x3C;/div>
        &#x3C;/details>
    &#x3C;/f:for>
&#x3C;/schema:type.fAQPage>

</section>

13.7 Breadcrumb Schema

Fluid ViewHelper Implementation

{namespace schema=Brotkrueml\Schema\ViewHelpers}

&#x3C;ol class="breadcrumb">
    &#x3C;f:for each="{breadcrumbs}" as="crumb" iteration="iter">
        &#x3C;li class="breadcrumb-item{f:if(condition: iter.isLast, then: ' active')}">
            &#x3C;f:if condition="{iter.isLast}">
                &#x3C;f:then>{crumb.title}&#x3C;/f:then>
                &#x3C;f:else>
                    &#x3C;a href="{crumb.url}">{crumb.title}&#x3C;/a>
                &#x3C;/f:else>
            &#x3C;/f:if>
        &#x3C;/li>
    &#x3C;/f:for>
&#x3C;/ol>

</nav>

13.8 Semantic HTML via Fluid Layouts

<!DOCTYPE html> <html lang="{siteLanguage.locale.languageCode}"> <head> <meta charset="UTF-8"> <meta name="viewport" content="width=device-width, initial-scale=1"> <f:render section="HeaderAssets" optional="true" /> </head> <body> <header role="banner"> <f:render partial="Header" /> </header>

&#x3C;nav role="navigation" aria-label="Main navigation">
    &#x3C;f:render partial="Navigation/Main" />
&#x3C;/nav>

&#x3C;main role="main">
    &#x3C;article>
        &#x3C;header>
            &#x3C;h1>{page.title}&#x3C;/h1>
            &#x3C;f:if condition="{page.subtitle}">
                &#x3C;p class="lead">{page.subtitle}&#x3C;/p>
            &#x3C;/f:if>
        &#x3C;/header>
        
        &#x3C;section>
            &#x3C;f:render section="Content" />
        &#x3C;/section>
    &#x3C;/article>
&#x3C;/main>

&#x3C;aside role="complementary">
    &#x3C;f:render partial="Sidebar" optional="true" />
&#x3C;/aside>

&#x3C;footer role="contentinfo">
    &#x3C;f:render partial="Footer" />
&#x3C;/footer>

</body> </html>

13.9 TYPO3 AI Search Optimization Checklist

Extensions & Configuration

EXT:seo installed and configured
EXT:schema (brotkrueml/schema ^4.2) installed
Static TypoScript templates included
robots.txt configured via site config with AI bot rules

Schema Implementation

Organization schema on all pages
Article schema on content pages
FAQPage schema on FAQ content
HowTo schema on tutorial content
BreadcrumbList on all pages
Author/Person schema with credentials

Content Structure

Semantic HTML5 elements in Fluid templates
Proper heading hierarchy (single H1)
Visible publication and update dates
Author bios with credentials
Alt text on all images via FAL

Technical

SYS_LASTCHANGED used for content freshness
Cache headers configured
XML sitemap via EXT:seo
Canonical URLs configured
hreflang for multi-language sites

13.10 Debugging Schema Output

Admin Panel Integration

EXT:schema integrates with TYPO3's Admin Panel. Enable it to see generated JSON-LD:

config/system/settings.php

$GLOBALS['TYPO3_CONF_VARS']['BE']['adminPanel'] = true;

Validation Tools

After implementing structured data, validate using:

Schema Markup Validator: https://validator.schema.org/
Google Rich Results Test: https://search.google.com/test/rich-results
Google Search Console: Submit and monitor structured data

View Generated JSON-LD

Fetch page and extract JSON-LD

curl -s https://example.com/page | grep -o '<script type="application/ld+json">.*</script>'

Markdown & MDX Implementation

This section covers AI search optimization for static sites and documentation platforms using Markdown (MD) and MDX.

14.1 Frontmatter for AI Search

Use frontmatter to define structured metadata that frameworks can transform into meta tags and structured data:

title: "How to Optimize Content for AI Search Engines" description: "Complete guide to AEO and GEO strategies for ChatGPT, Perplexity, and Google AI Overviews visibility." date: 2025-01-15 lastmod: 2025-01-15 author: name: "Jane Doe" title: "SEO Specialist" linkedin: "https://linkedin.com/in/janedoe" twitter: "https://twitter.com/janedoe" tags: ["aeo", "geo", "ai-search", "seo"] category: "SEO" image: "/images/ai-search-guide.jpg" schema: type: "Article" wordCount: 2500 draft: false

14.2 Content Structure Best Practices

Main Topic as H1 (Single, Contains Primary Question/Keyword)

Brief 2-3 sentence summary answering the main question directly. This paragraph is what AI engines extract first.

What is [Topic]?

Direct definition in 1-2 sentences. [Topic] is...

Key Characteristics

Point 1: Specific, factual information
Point 2: Verifiable data with source
Point 3: Actionable insight

How Does [Topic] Work?

Clear process explanation.

First step with expected outcome
Second step with verification
Third step with result

Why is [Topic] Important?

Benefit	Impact	Evidence
Benefit 1	Measurable result	Source/study
Benefit 2	Specific outcome	Data point

Frequently Asked Questions

<details> <summary>Question 1?</summary>

Direct answer to question 1.

</details>

<details> <summary>Question 2?</summary>

Direct answer to question 2.

</details>

14.3 JSON-LD in MDX (Next.js / Astro)

Next.js App Router

// components/JsonLd.tsx type JsonLdProps = { data: Record<string, unknown>; };

export function JsonLd({ data }: JsonLdProps) { return ( <script type="application/ld+json" dangerouslySetInnerHTML={{ __html: JSON.stringify(data).replace(/</g, '\u003c'), }} /> ); }

title: "AI Search Optimization Guide"

import { JsonLd } from '@/components/JsonLd';

AI Search Optimization Guide

Content here...

Astro with astro-seo-schema

npm install schema-dts astro-seo-schema

// src/layouts/Article.astro import { Schema } from 'astro-seo-schema'; const { frontmatter } = Astro.props;

14.4 FAQ Schema Component for MDX

// components/FAQ.tsx import { JsonLd } from './JsonLd';

type FAQItem = { question: string; answer: string; };

type FAQProps = { items: FAQItem[]; };

export function FAQ({ items }: FAQProps) { const schemaData = { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": items.map(item => ({ "@type": "Question", "name": item.question, "acceptedAnswer": { "@type": "Answer", "text": item.answer } })) };

return ( <> <JsonLd data={schemaData} /> <section className="faq"> {items.map((item, index) => ( <details key={index}> <summary>{item.question}</summary> <p>{item.answer}</p> </details> ))} </section> </> ); }

import { FAQ } from '@/components/FAQ';

Frequently Asked Questions

14.5 Raw MDX View with URL Parameter

Enable viewing raw MDX source for transparency and AI training accessibility:

Next.js Implementation

// next.config.js - Rewrite .md URLs to API module.exports = { async rewrites() { return [ { source: '/docs/:path*.md', destination: '/api/raw-mdx?path=:path*', }, ]; }, };

// app/api/raw-mdx/route.ts import { NextRequest, NextResponse } from 'next/server'; import fs from 'fs'; import path from 'path';

export async function GET(request: NextRequest) { const searchParams = request.nextUrl.searchParams; const filePath = searchParams.get('path');

if (!filePath) { return NextResponse.json({ error: 'Path required' }, { status: 400 }); }

// Prevent directory traversal const safePath = filePath.replace(/../g, ''); const mdxPath = path.join(process.cwd(), 'content', ${safePath}.mdx);

try { const content = fs.readFileSync(mdxPath, 'utf8'); return new NextResponse(content, { headers: { 'Content-Type': 'text/plain; charset=utf-8' }, }); } catch { return NextResponse.json({ error: 'Not found' }, { status: 404 }); } }

Usage:

/docs/getting-started → Rendered page
/docs/getting-started.md → Raw MDX source

Query Parameter Alternative

// app/docs/[...slug]/page.tsx import { notFound } from 'next/navigation'; import fs from 'fs'; import path from 'path';

type Props = { params: { slug: string[] }; searchParams: { raw?: string }; };

export default async function Page({ params, searchParams }: Props) { const slug = params.slug.join('/'); const mdxPath = path.join(process.cwd(), 'content', ${slug}.mdx);

// Show raw MDX if ?raw=true if (searchParams.raw === 'true') { try { const rawContent = fs.readFileSync(mdxPath, 'utf8'); return ( <article> <header> <p className="text-sm text-gray-500"> Raw MDX source • <a href={/docs/${slug}}>View rendered</a> </p> </header> <pre className="p-4 bg-gray-50 rounded overflow-auto"> <code>{rawContent}</code> </pre> </article> ); } catch { notFound(); } }

// Normal MDX rendering // ... your MDX processing }

Usage:

/docs/getting-started → Rendered page
/docs/getting-started?raw=true → Raw MDX source

14.6 Automatic Schema Generation from Frontmatter

// lib/generateSchema.ts type Frontmatter = { title: string; description: string; date: string; lastmod?: string; author?: { name: string; title?: string; linkedin?: string; twitter?: string; }; image?: string; schema?: { type?: 'Article' | 'HowTo' | 'FAQPage'; wordCount?: number; }; };

export function generateSchema(frontmatter: Frontmatter, url: string) { const schemaType = frontmatter.schema?.type || 'Article';

const baseSchema = { "@context": "https://schema.org", "@type": schemaType, "headline": frontmatter.title, "description": frontmatter.description, "url": url, "datePublished": frontmatter.date, "dateModified": frontmatter.lastmod || frontmatter.date, };

if (frontmatter.author) { const sameAs = [ frontmatter.author.linkedin, frontmatter.author.twitter, ].filter(Boolean);

baseSchema["author"] = {
  "@type": "Person",
  "name": frontmatter.author.name,
  "jobTitle": frontmatter.author.title,
  ...(sameAs.length > 0 &#x26;&#x26; { "sameAs": sameAs }),
};

}

if (frontmatter.image) { baseSchema["image"] = frontmatter.image; }

if (frontmatter.schema?.wordCount) { baseSchema["wordCount"] = frontmatter.schema.wordCount; }

return baseSchema; }

14.7 MD/MDX AI Search Checklist

Frontmatter: Title, description, date, lastmod, author with credentials
Structure: Single H1, logical heading hierarchy, direct answers first
Schema: JSON-LD in layout or per-page (Article, FAQPage, HowTo)
FAQ sections: Use <details>/<summary> with FAQPage schema
Tables: For comparisons (AI extracts structured data)
Lists: Bullet points and numbered steps
Last modified: Visible and in frontmatter
Author bio: Name, credentials, social links
Raw view: Optional .md or ?raw=true endpoint
Images: Alt text, proper dimensions, WebP format
llms.txt: LLM-friendly site index (see Section 15)

llms.txt - LLM Site Index

The llms.txt standard provides a structured, machine-readable file to help LLMs understand and navigate your website content efficiently.

Note: As of late 2025, adoption by major AI companies is still limited, but implementing llms.txt is low-effort and future-proofs your site for AI discovery.

15.1 What is llms.txt?

Similar to robots.txt for crawlers, llms.txt is a Markdown file at your site root that:

Provides a concise index of key documentation/pages
Includes descriptions to help LLMs understand content purpose
Enables AI tools to find relevant content without parsing your entire site
Supports an optional llms-full.txt with complete documentation

15.2 Basic llms.txt Format

Your Company Name

Brief one-sentence description of your site/product.

Additional context about the site, target audience, and how to use this index.

Documentation

Getting Started: Quick introduction for new users
API Reference: Complete API documentation with examples
Configuration Guide: Setup and configuration options

Tutorials

Building Your First App: Step-by-step beginner guide
Advanced Patterns: In-depth exploration of features

Optional

About Us: Company background and team
Blog: Latest news and articles
Changelog: Version history and updates

Key rules:

Single H1 (# ) with site/project name
Blockquote (> ) with brief description
H2 sections (## ) for content groups
Links formatted as Title: Description
Optional

section for content LLMs can skip

15.3 llms-full.txt - Complete Documentation

For sites with extensive documentation, provide a llms-full.txt containing your entire documentation in a single Markdown file:

Your Company Documentation

Complete documentation for Your Company's platform.

Getting Started

[Full content of getting started page...]

API Reference

Authentication

[Full API auth documentation...]

Endpoints

[Full API endpoints documentation...]

Configuration

[Full configuration documentation...]

Use cases:

AI coding assistants need full API context
Complex integrations require complete documentation
Technical support AI needs comprehensive knowledge base

15.4 TYPO3 Implementation

TYPO3 has a dedicated extension for llms.txt generation:

Install the extension (TYPO3 v13+)

ddev composer require web-vision/ai-llms-txt

Site Configuration

config/sites/main/config.yaml

imports:

resource: 'EXT:ai_llms_txt/Configuration/Routes/RouterEnhancer.yaml'

TypoScript Configuration

Include extension TypoScript

@import 'EXT:ai_llms_txt/Configuration/TypoScript/setup.typoscript'

Custom configuration

plugin.tx_aillmstxt { settings { # Pages to include (comma-separated UIDs or "auto") includePages = auto

    # Exclude specific pages
    excludePages = 1,2,3
    
    # Include page types
    includeDoktypes = 1,4
    
    # Maximum depth
    maxDepth = 3
}

}

Manual llms.txt via Static Route

For full control, create a static route:

config/sites/main/config.yaml

routes:

route: llms.txt type: staticText content: |

Your TYPO3 Site

Enterprise content management and digital experience platform.

Main Sections
- Home: Main landing page
- Products: Our product catalog
- Documentation: Technical documentation
- Blog: Latest articles and news
Optional
- About Us: Company information
- Contact: Get in touch

15.5 Next.js Implementation

Static File (Simple)

Your Next.js App

Modern web application built with Next.js.

Documentation

${docs.map(doc => - [${doc.title}](/docs/${doc.slug}): ${doc.description}).join('\n')}

Blog

${posts.slice(0, 10).map(post => - [${post.title}](/blog/${post.slug}): ${post.excerpt}).join('\n')}

Optional

About: About us
Contact: Get in touch `;

return new Response(content, { headers: { 'Content-Type': 'text/plain; charset=utf-8', 'Cache-Control': 'public, max-age=3600, must-revalidate', }, }); }

llms-full.txt Generation

// app/llms-full.txt/route.ts import { getDocPages } from '@/lib/content'; import fs from 'fs'; import path from 'path';

export async function GET() { const docs = await getDocPages();

let fullContent = `# Complete Documentation

Full documentation for Your Site.

for (const doc of docs) { const mdxPath = path.join(process.cwd(), 'content/docs', ${doc.slug}.mdx); try { const content = fs.readFileSync(mdxPath, 'utf8'); // Remove frontmatter const cleanContent = content.replace(/^---[\s\S]*?---\n/, ''); fullContent += ---\n\n## ${doc.title}\n\n${cleanContent}\n\n; } catch { // Skip if file not found } }

return new Response(fullContent, { headers: { 'Content-Type': 'text/plain; charset=utf-8', 'Cache-Control': 'public, max-age=3600, must-revalidate', }, }); }

15.6 Astro Implementation

Using Integration

npm install @waldheimdev/astro-ai-llms-txt

// astro.config.mjs import llmsTxt from '@waldheimdev/astro-ai-llms-txt';

export default { integrations: [ llmsTxt({ projectName: 'Your Project', description: 'Your project description.', site: 'https://your-domain.com', }), ], };

Manual API Route

// src/pages/llms.txt.ts import { getCollection } from 'astro:content'; import type { APIRoute } from 'astro';

export const GET: APIRoute = async () => { const docs = await getCollection('docs'); const blog = await getCollection('blog');

const content = `# Your Astro Site

Static site built with Astro.

Documentation

${docs.map(doc => - [${doc.data.title}](/docs/${doc.slug}): ${doc.data.description}).join('\n')}

Blog

${blog.slice(0, 10).map(post => - [${post.data.title}](/blog/${post.slug}): ${post.data.excerpt}).join('\n')} `;

return new Response(content, { headers: { 'Content-Type': 'text/plain; charset=utf-8' }, }); };

15.7 llms.txt Best Practices

Aspect Recommendation

File size Keep under 50KB for efficient parsing

Descriptions Brief, informative (not marketing copy)

Links Use absolute URLs for external consumption

Updates Regenerate on content changes

Sections Group logically (Docs, API, Tutorials, Optional)

Optional section Mark non-essential content LLMs can skip

15.8 llms.txt Checklist

llms.txt at site root with structured index
H1 heading with site/project name
Blockquote summary describing the site
Organized sections (Docs, API, Blog, Optional)
Link descriptions for each URL
llms-full.txt for documentation-heavy sites (optional)
Cache headers set appropriately (1 hour recommended)
UTF-8 encoding with text/plain content type

Resources & References

Official Documentation

Google AI Overviews Guidelines
Schema.org Full Hierarchy
OpenAI GPTBot Documentation
llms.txt Specification
TYPO3 EXT:ai_llms_txt Documentation

Industry Resources

Semrush AI Search Study
Ahrefs AI Impact on SEO

Monitoring Tools

Semrush AI Visibility Checker
Brand24 AI Brand Visibility
SE Ranking AI Visibility Tracker

Credits & Attribution

This skill synthesizes best practices from industry research by Microsoft Advertising, Semrush, Ahrefs, and the broader SEO community's work on generative engine optimization.

Key sources:

Microsoft Advertising: "From Discovery to Influence: A Guide to AEO and GEO"
Semrush research on AI search content optimization
Ahrefs analysis of AI impact on SEO

Created by webconsulting.at for the Claude Cursor Skills collection.

ai-search-optimization

Safety Notice

Copy this and send it to your AI assistant to learn

H1: Main Topic (contains primary question/keyword)

Content Freshness Checklist

Weekly Tasks

Monthly Tasks

Quarterly Tasks

robots.txt - AI Search Optimization

Standard search engines

OpenAI (ChatGPT)

Perplexity AI

Anthropic (Claude)

Google AI (Gemini)

Meta AI

Common Crawl (used by many AI systems)

Microsoft/Bing AI

Default rule

Sitemap

BLOCK: AI model training (your content won't train future AI)

ALLOW: Real-time AI search (AI can cite you in answers)

What is [Topic]?

Key characteristics:

How does [Topic] work?

Step-by-step breakdown:

Why is [Topic] important?

Benefits include:

Monthly AI Visibility Audit

Test Queries (adapt to your niche)

Platforms to Test

Record for Each Query

Quarterly Review Checklist

AI Platform Updates

Content Strategy

Technical Updates

Core SEO extension (meta tags, sitemaps, canonicals)

Schema.org structured data (essential for AI search)

Version constraint ensures v13/v14 compatibility

Optional: Extended SEO features (v13/v14 compatible)

In Composer mode, extensions are auto-activated

Verify installation:

config/sites/main/config.yaml

Standard search engines

OpenAI (ChatGPT)

Perplexity AI

Anthropic (Claude)

Google AI (Gemini)

Meta AI

Common Crawl (used by many AI systems)

Default

Expose last modified date in HTTP headers

Display last updated date in content

ContentBlocks/ContentElements/faq-accordion/config.yaml

config/system/settings.php

Fetch page and extract JSON-LD

Main Topic as H1 (Single, Contains Primary Question/Keyword)

What is [Topic]?

Key Characteristics

How Does [Topic] Work?

Why is [Topic] Important?

Frequently Asked Questions

title: "AI Search Optimization Guide"

AI Search Optimization Guide

// src/layouts/Article.astro import { Schema } from 'astro-seo-schema'; const { frontmatter } = Astro.props;

Frequently Asked Questions

Your Company Name

Documentation

Tutorials

Optional

Optional

Your Company Documentation

Getting Started

API Reference

Authentication

Endpoints

Configuration

Install the extension (TYPO3 v13+)

config/sites/main/config.yaml

Include extension TypoScript

Custom configuration