Optimize content for AI search engines — ChatGPT, Perplexity, Claude, Gemini, and AI Overviews. Covers entity optimization, structured data, citation-worthy formatting, and platform-specific strategies. Use when someone wants visibility in AI-generated answers, says 'AI SEO', 'AI search', 'LLM optimization', 'ChatGPT ranking', 'Perplexity citations', 'AI Overviews', or wants their content cited by AI assistants. The new SEO frontier — if you're only optimizing for Google, you're already behind.
Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.
Une commande directe contourne le prompt de vérification. Examinez la source avant de l'exécuter.
Optimize content for AI search engines — ChatGPT, Perplexity, Claude, Gemini, and AI Overviews. Covers entity optimization, structured data, citation-worthy formatting, and platform-specific strategies. Use when someone wants visibility in AI-generated answers, says 'AI SEO', 'AI search', 'LLM optimization', 'ChatGPT ranking', 'Perplexity citations', 'AI Overviews', or wants their content cited by AI assistants. The new SEO frontier — if you're only optimizing for Google, you're already behind.
["ai seo","ai search","perplexity","chatgpt ranking","ai overview","answer engine","llmo","geo","aeo","cited by ai","ai visibility","ai optimization"]
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AI SEO Optimization
You optimize content so AI search engines — ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews — cite, reference, and recommend it. Traditional SEO gets you on page one of Google. AI SEO gets you into the AI's answer.
This is a different game. AI engines don't rank pages — they synthesize answers from sources they trust. Your job is to become a source they trust and cite.
On Activation
Read brand/ directory: load voice-profile.md, keyword-plan.md, positioning.md, competitors.md if present.
Show what loaded:
Backend Selection
Prefer OpenSEO get_ranked_keywords / get_serp_results (and AI-search MCP tools when exposed) when configured; otherwise crawl/Exa with ranking data unknown. Full contract: skills/openseo/references/backend-contract.md.
If no brand files exist, ask: What topics do you want AI engines to cite you for? Who are your competitors in AI results?
Determine mode: Audit (assess current AI visibility) or Optimize (improve content for AI citation).
If keyword plan exists, flag which queries are likely AI-dominated (how-to, what-is, comparison queries).
How AI Search Works (The Mental Model)
Traditional search: User types query → Google ranks pages → user clicks a link
AI search: User asks question → AI reads sources → AI synthesizes answer → cites sources inline
What this means for you:
You're not competing for clicks. You're competing to be a cited source.
AI engines favor content that directly, clearly, authoritatively answers questions.
Structure and clarity matter more than keyword density.
Being cited once compounds — AI engines build entity graphs that persist.
Playbook Pages = AI-Citation Surface Area
The single highest-leverage page format for AI-citation is the long-form playbook — 2,500+ word pillar content with Article + HowTo JSON-LD, named author, dateModified, and step-based structure. AI engines (ChatGPT search, Perplexity, Claude, Gemini, Google AI Overviews) preferentially cite playbook-pattern pages over short blog posts because:
Why playbooks win citations
Detail
Step-based structure
HowTo schema makes the answer machine-extractable; AI engines lift the steps verbatim
Named author + entity
Author bio with sameAs links to social profiles compounds the entity graph
Concrete numbers
Specific stats ("73% of B2B SaaS under 50 employees post less than once a week") get cited; vague claims ("most companies struggle") don't
Counter-arguments inline
AI engines reward sources that show "thinking" — playbooks with "don't do X because Y" sections demonstrate authority
dateModified discipline
Recent modification dates signal freshness; AI engines deprecate stale sources
Tie-in with seo-machine: if you're running a programmatic sprint, ship playbook pages as Phase 4+ (after alternatives/compare/use-case ship first for conversion). seo-machine Pattern E is the playbook pipeline — pair it with this skill's entity-optimization and FAQ-formatting recipes to maximize citation surface area.
Avoid for AI-citation: generic blog posts with no schema, content without a named author, listicles without a clear "do this not that" stance, pages that hedge every claim with "it depends." These rank but don't get cited.
Brand Integration
voice-profile.md → Author entity recognition in AI engines depends on consistent voice across all content. AI engines build brand models from repeated patterns — voice consistency IS an SEO signal.
keyword-plan.md → Target queries where the brand has genuine authority. AI engines cite sources that demonstrate expertise, not just keyword density.
Step 1: AI Visibility Audit
Check Current AI Presence
Use available tools to test AI visibility. Not all engines will be testable — audit what you can, note what you can't.
With browser tool available:
Perplexity: Navigate to perplexity.ai, search "[your topic]" — check if pages appear in sources
Google AI Overviews: Search on google.com — check if brand appears in AI Overview
Search for "[brand] + [topic]" to assess web presence that AI engines index
Check if key pages appear in top results (AI engines favor high-ranking pages)
Search for competitor content on the same topics to benchmark
Without browser or web search:
Review existing content structure against AI citation patterns (see references/content-patterns.md)
Check schema markup on existing pages
Audit content formatting for extractability
Note limitation: "Live AI visibility testing requires browser access. This audit covers content optimization only."
Audit Output
Query
ChatGPT
Perplexity
AI Overview
Claude
Status
[query 1]
Not cited
Source #3
Not included
Mentioned
Partial
[query 2]
Recommended
Source #1
Featured
Named
Strong
[query 3]
Not mentioned
Not found
Not included
Not mentioned
Absent
For each "Absent" or "Partial" query, create an optimization plan.
Step 2: Entity Optimization
AI engines understand entities (people, brands, products, concepts), not just keywords. You need to establish your entity clearly.
Build Your Entity Profile
Ensure these exist and are consistent across the web:
Wikipedia / Wikidata: If eligible, create or update your entry
Crunchbase: Company profile with accurate data
LinkedIn: Complete company and founder profiles
Schema.org markup: Organization, Person, Product schemas on your site
About page: Clear, factual, third-person description of who you are and what you do
Author pages: Every content creator has a page with credentials, links, and bio
Entity Signals to Strengthen
Signal
Action
Consistent naming
Use the exact same brand name everywhere — no variations
Co-occurrence
Get mentioned alongside known entities in your space
Structured data
Organization + Person + Product schema on every relevant page
Backlinks from authorities
Citations from sites AI engines already trust
Cross-platform presence
Same entity info on LinkedIn, Twitter, GitHub, Crunchbase
Step 3: Content Optimization for AI Citation
The Definitive Answer Pattern
AI engines prefer content structured as clear, authoritative answers. For every target query:
## [Question as H2]
[Direct answer in 1-2 sentences — this is what gets cited]
[Supporting detail, evidence, examples in 2-4 paragraphs]
[Data or specific numbers that add credibility]
This pattern works because:
AI engines can extract the direct answer for synthesis
The supporting detail gives the AI confidence in your authority
Specific data makes your content more citable than vague competitors
Question-Answer Formatting
Structure content to match how people ask AI engines questions:
Identify conversational queries:
"What is the best [X] for [Y]?"
"How do I [accomplish Z]?"
"What's the difference between [A] and [B]?"
"[X] vs [Y] — which should I choose?"
"Why does [thing] happen?"
For each query, create a section that:
Uses the question (or close variant) as the heading
Answers directly in the first sentence
Provides supporting evidence
Includes specific numbers, dates, or examples
Links to primary sources when citing claims
FAQ Sections
Add FAQ sections with structured data to every key page:
## Frequently Asked Questions### [Exact question someone would ask an AI]
[Direct, authoritative answer. 2-4 sentences. Include a specific fact or number.]
### [Next question]
[Direct answer.]
Add FAQPage schema markup to every FAQ section.
Step 4: Structured Data for AI
Required Schema Types
Schema
Purpose
AI Engine Benefit
Organization
Establish entity
All engines — entity recognition
Person (authors)
Author authority
Perplexity, Google AI — source credibility
Article
Content metadata
All engines — content classification
FAQPage
Q&A content
Google AI Overviews — direct extraction
HowTo
Process content
Google AI Overviews — step extraction
Product
Product info
ChatGPT, Perplexity — recommendation queries
Review
Credibility signal
All engines — trust signal
Implementation
Every page should have at minimum:
Organization schema (site-wide)
Article + Person schema (all content pages)
FAQPage schema (any page with Q&A content)
BreadcrumbList schema (all pages)
Step 5: Citation-Friendly Formatting
AI engines are more likely to cite content that is easy to parse and extract from.
Short paragraphs: 2-3 sentences max, one idea per paragraph
Definition patterns: "X is [clear definition]." — direct, extractable
Comparison tables: AI engines love structured comparisons
Numbered lists: Steps, rankings, processes — easy to extract
Data presentation: Tables > prose for statistics and comparisons
Primary source citations: Link to studies, reports, official docs
Last updated dates: Show freshness — AI engines prefer recent content
What AI Engines Trust
Trust Signal
How to Implement
Author expertise
Author page with credentials, experience, publications
Original research
Proprietary data, surveys, case studies
External citations
Cite reputable sources, link to primary research
Freshness
Regular updates, current year stats, "last updated" dates
Depth
Comprehensive coverage that other sources lack
Specificity
Exact numbers, dates, examples over vague claims
Consistency
Same facts across your site, no contradictions
Step 6: Platform-Specific Strategies
Perplexity
Perplexity heavily indexes web content and favors clear, structured pages
Strong source attribution — your URL appears next to cited text
Optimize for question-based queries with direct answers
Technical content and comparisons perform well
ChatGPT (with browsing)
Browses the web for current information
Favors authoritative, well-structured content
Brand mentions in trusted sources increase recommendation likelihood
Product/comparison pages get cited for "best X" queries
Google AI Overviews
Pulls from existing Google index — traditional SEO still matters
Favors content that directly answers the query in 2-3 sentences
FAQ schema content frequently appears in AI Overviews
How-to and listicle formats are heavily extracted
Claude
Knowledge is training-based (less real-time web access)
Entity recognition from web-scale training data
Being mentioned across many trusted sources increases recognition
Wikipedia, major publications, and authoritative sites have outsized impact
Step 7: Monitoring and Iteration
Monthly AI Visibility Check
Re-run the audit queries across all AI engines
Track changes in citation status
Identify new queries where AI engines are active in your space
Update content that lost AI visibility
Create new content for queries where you're absent
Tracking Sheet
| Month | Query | Engine | Status | Action Taken | Result |
|-------|-------|--------|--------|-------------|--------|
| Mar 2026 | "best X for Y" | Perplexity | Source #5 | Added comparison table | TBD |
| Mar 2026 | "how to Z" | ChatGPT | Not cited | Created definitive answer | TBD |
Key Differences from Traditional SEO
Traditional SEO
AI SEO
Optimize for keywords
Optimize for questions and entities
Compete for page 1 ranking
Compete to be a cited source
Keyword density matters
Answer clarity matters
Backlinks drive authority
Being mentioned across trusted sources drives authority
Meta tags for CTR
Structured data for extraction
Content length signals depth
Answer directness signals usefulness
One-time optimization
Continuous monitoring across multiple engines
Anti-Patterns
Traditional SEO is the foundation AI SEO sits on. AI engines pull from web indexes — if your pages aren't ranking or indexed, they can't be cited. Check traditional SEO basics (/seo-audit) before investing in AI-specific optimization.
FAQ schema only works when it matches real Q&A content. Google penalizes schema that doesn't reflect what's visible on the page. Add FAQPage markup to pages with genuine questions and answers, not as a blanket optimization.
AI citation is volatile — a single test proves nothing. A page cited this week may drop next month as AI models update their indexes and weights. The monitoring step (Step 7) exists because ongoing tracking is the only way to maintain AI visibility.
Write for humans, format for AI. Over-optimizing for extractability (robotic, formulaic answers) hurts traditional SEO and user trust. The best AI-cited content is genuinely useful content that happens to be well-structured.
Robots.txt is the gatekeeper. If AI bots (GPTBot, PerplexityBot, ClaudeBot) are blocked, no amount of content optimization matters. This is the very first thing to check — see references/platform-ranking-factors.md for the full bot list.
Error States
No web search or browser available: Skip live audit (Step 1), proceed with content optimization (Steps 2-6) using existing content analysis. Note: "AI visibility audit requires browser or web search. Content optimization complete — recommend live audit when tools are available."
No brand files exist: Ask for target topics and competitors directly. Proceed with generic optimization. Suggest running /brand-voice and /keyword-research first.
No existing content to optimize: Shift to content planning mode — create the ai-seo-content-plan.md with priority queries and content specs. Suggest /seo-content to create the actual content.
Can't access AI engines for testing: Focus on content structure, schema markup, and formatting optimization. Flag that live testing is deferred.
