AI Discovery Expert Skill

Expert-level optimization for AI-powered search engines and answer engines. Covers Perplexity, ChatGPT Search, Gemini, Claude, and other LLM-based discovery platforms.

Auto-Detection

This skill activates when:

• Discussing AI search engines (Perplexity, ChatGPT Search, Gemini)

• Optimizing content for LLM citation and discovery

• Implementing AI-friendly content structures

• Working on answer engine optimization (AEO)

• Discussing generative search and AI crawlers

1. AI Discovery vs Traditional SEO

comparison[4]{aspect,traditional_seo,ai_discovery}: Goal,Rank on SERP position 1-10,Get cited in AI answers Format,Keywords + backlinks,Clear answers + structured data Content,Keyword density,Comprehensive + authoritative Measurement,Rankings + clicks,Citations + brand mentions

Key Insight

AI search engines synthesize answers from multiple sources. Your goal is to be cited as an authoritative source, not just ranked.

2. Content Structure for AI Citation

Answer-First Writing

<!-- ✅ GOOD: Direct answer first -->

What is Server-Side Rendering (SSR)?

Server-Side Rendering (SSR) is a technique where web pages are rendered on the server and sent as fully-formed HTML to the browser. This improves initial page load time and SEO compared to client-side rendering.

How SSR Works

1. User requests a page
2. Server renders the HTML
3. Browser receives complete HTML
4. JavaScript hydrates for interactivity

<!-- ❌ BAD: Buried answer -->

Understanding Modern Web Development

In the evolving landscape of web development, there are many techniques... [500 words later] ...which brings us to Server-Side Rendering (SSR).

Structured Answer Patterns

answer_patterns[5]{pattern,usage,example}: Definition first,Concepts/terms,"X is a technique that..." Step-by-step,How-to guides,"1. First... 2. Then... 3. Finally..." Comparison tables,Alternatives,Feature comparison grids Pro/con lists,Decision making,"Pros: ... Cons: ..." FAQ format,Common questions,"Q: What is? A: It is..."

3. AI-Optimized Content Formats

Comprehensive FAQ Sections

<!-- Structured for both SEO and AI --> <section itemscope itemtype="https://schema.org/FAQPage"> <h2>Frequently Asked Questions</h2>

<div itemscope itemprop="mainEntity" itemtype="https://schema.org/Question"> <h3 itemprop="name">What is the best framework for SSR?</h3> <div itemscope itemprop="acceptedAnswer" itemtype="https://schema.org/Answer"> <p itemprop="text"> Next.js is widely considered the best framework for SSR due to its built-in support for server components, automatic code splitting, and excellent developer experience. Alternatives include Nuxt.js for Vue and SvelteKit for Svelte. </p> </div> </div> </section>

Authoritative Data Tables

<!-- Tables are easily parsed by AI --> <table> <caption>SSR Framework Comparison 2025</caption> <thead> <tr> <th>Framework</th> <th>Language</th> <th>Performance</th> <th>Learning Curve</th> </tr> </thead> <tbody> <tr> <td>Next.js</td> <td>React/TypeScript</td> <td>Excellent</td> <td>Medium</td> </tr> <tr> <td>Nuxt.js</td> <td>Vue/TypeScript</td> <td>Excellent</td> <td>Easy</td> </tr> </tbody> </table>

4. Entity Optimization (Critical for AI)

Build Topic Authority

entity_signals[5]{signal,implementation}: Author entities,Author pages with credentials + schema Organization entities,About page with company schema Topic clusters,Hub pages linking to detailed subtopics External mentions,Citations from authoritative sources Consistent naming,Same entity names across all content

Author Schema for E-E-A-T

{ "@context": "https://schema.org", "@type": "Person", "@id": "https://example.com/authors/john-doe#person", "name": "John Doe", "jobTitle": "Senior Software Engineer", "description": "10+ years experience in web development, contributor to React and Next.js", "url": "https://example.com/authors/john-doe", "sameAs": [ "https://twitter.com/johndoe", "https://github.com/johndoe", "https://linkedin.com/in/johndoe" ], "knowsAbout": [ "React", "Next.js", "Server-Side Rendering", "Web Performance" ], "alumniOf": { "@type": "Organization", "name": "MIT" }, "worksFor": { "@type": "Organization", "name": "Company Name" } }

5. Semantic HTML for AI Parsing

Clear Content Hierarchy

<!-- ✅ GOOD: Clear semantic structure --> <article> <header> <h1>Complete Guide to Server-Side Rendering</h1> <p class="summary"> Learn how SSR improves performance and SEO for modern web apps. </p> <time datetime="2025-01-15">January 15, 2025</time> </header>

<nav aria-label="Table of contents"> <h2>Contents</h2> <ol> <li><a href="#what-is-ssr">What is SSR?</a></li> <li><a href="#benefits">Benefits of SSR</a></li> <li><a href="#implementation">Implementation Guide</a></li> </ol> </nav>

<section id="what-is-ssr"> <h2>What is SSR?</h2> <p>Server-Side Rendering is...</p> </section>

<section id="benefits"> <h2>Benefits of SSR</h2> <ul> <li>Faster initial page load</li> <li>Better SEO performance</li> <li>Improved accessibility</li> </ul> </section>

<aside> <h3>Related Articles</h3> <ul> <li><a href="/static-generation">Static Site Generation</a></li> <li><a href="/client-rendering">Client-Side Rendering</a></li> </ul> </aside> </article>

6. AI Crawler Considerations

Perplexity Bot

robots.txt - Allow Perplexity

User-agent: PerplexityBot Allow: / Crawl-delay: 1

Common AI Crawlers

ai_crawlers[6]{bot,engine,recommendation}: GPTBot,OpenAI/ChatGPT,Allow for AI search visibility Google-Extended,Google Gemini,Allow for Gemini citations PerplexityBot,Perplexity,Allow - major AI search engine ClaudeBot,Anthropic Claude,Allow for Claude citations Applebot-Extended,Apple Intelligence,Allow for Apple AI features CCBot,Common Crawl,Allow - trains many AI models

Recommended robots.txt

Allow major AI crawlers for discovery

User-agent: GPTBot Allow: /

User-agent: Google-Extended Allow: /

User-agent: PerplexityBot Allow: /

User-agent: ClaudeBot Allow: /

User-agent: Applebot-Extended Allow: /

Block training-only crawlers if desired

User-agent: CCBot Disallow: /

Standard search engines

User-agent: Googlebot Allow: /

User-agent: Bingbot Allow: /

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

7. Content Freshness Signals

Keep-Current Patterns

// Show last updated date prominently <article> <header> <h1>Next.js SEO Guide</h1> <div className="meta"> <time dateTime="2025-01-15"> Last updated: January 15, 2025 </time> <span>Originally published: March 2024</span> </div> </header> </article>

// Add update log for major changes <section> <h2>Update History</h2> <ul> <li><strong>Jan 2025:</strong> Added Next.js 15 features</li> <li><strong>Oct 2024:</strong> Updated for App Router changes</li> <li><strong>Mar 2024:</strong> Initial publication</li> </ul> </section>

Schema with Dates

{ "@type": "Article", "datePublished": "2024-03-15T08:00:00+00:00", "dateModified": "2025-01-15T10:30:00+00:00" }

8. Citation-Worthy Content Patterns

What Gets Cited

citation_factors[6]{factor,why}: Original research,Unique data AI can't find elsewhere Expert opinions,Authoritative perspectives Concrete numbers,Statistics and benchmarks Step-by-step guides,Actionable how-to content Comparison tables,Structured decision-making data Definition sections,Clear explanations of concepts

Content Quality Signals

quality_signals[5]{signal,implementation}: Expertise,Author credentials + experience displayed Sources,Citations to authoritative references Comprehensiveness,Cover topic fully with depth Recency,Regular updates with visible dates Uniqueness,Original insights not found elsewhere

9. LLM.txt Standard (Emerging)

What is llm.txt?

A proposed standard (like robots.txt) specifically for AI/LLM consumption.

llm.txt - AI-specific instructions

Place at site root: https://example.com/llm.txt

Site identity

name: Example Tech Blog description: Expert guides on web development and JavaScript frameworks author: Example Team contact: hello@example.com

Content focus

topics: React, Next.js, TypeScript, Web Performance, SEO

Citation preferences

citation-name: Example Tech Blog citation-url: https://example.com

Content freshness

update-frequency: weekly last-major-update: 2025-01-15

Preferred citation format

cite-as: "According to Example Tech Blog..."

Key resources for AI understanding

resources:

• /about - Company and author information
• /glossary - Technical term definitions
• /guides - Comprehensive tutorials

10. Monitoring AI Citations

Track Brand Mentions

monitoring_tools[4]{tool,purpose}: Perplexity,Search your brand - see if cited ChatGPT,Ask about your topic - check citations Google Alerts,Monitor brand mentions across web BrandMentions,Track citations in AI responses

Manual Testing Prompts

Test queries to check AI citations:

1. "What is [your topic]?" - Check if your definition is cited
2. "Best [your product category]" - Check if you appear in recommendations
3. "How to [task you teach]" - Check if your guide is referenced
4. "[Your brand name] review" - Check brand awareness

Quick Reference Checklist

ai_discovery_checklist[12]{check,priority}: Answer-first content structure,Critical Clear semantic HTML hierarchy,Critical Comprehensive FAQ sections,High Author/organization schema,High Allow AI crawlers in robots.txt,High Visible update dates,High Original research/data,High Structured comparison tables,Medium Topic cluster architecture,Medium External authority signals,Medium llm.txt file (emerging),Low Citation monitoring setup,Low

Related Skills

• seo-expert

• Traditional search engine optimization

• ui-expert

• Frontend implementation

• nextjs-expert

• Next.js metadata implementation

Version: 1.0.0