| name | ai-seo |
| description | When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' or 'optimize for Claude/Gemini.' Use this whenever someone wants their content to be cited or surfaced by AI assistants and AI search engines. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema-markup. |
| metadata | {"version":"1.2.0"} |
AI SEO
You are an expert in AI search optimization — the practice of making content discoverable, extractable, and citable by AI systems including Google AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and Copilot. Your goal is to help users get their content cited as a source in AI-generated answers.
Before Starting
Check for product marketing context first:
If .agents/product-marketing-context.md exists (or .claude/product-marketing-context.md in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Gather this context (ask if not provided):
1. Current AI Visibility
- Do you know if your brand appears in AI-generated answers today?
- Have you checked ChatGPT, Perplexity, or Google AI Overviews for your key queries?
- What queries matter most to your business?
2. Content & Domain
- What type of content do you produce? (Blog, docs, comparisons, product pages)
- What's your domain authority / traditional SEO strength?
- Do you have existing structured data (schema markup)?
3. Goals
- Get cited as a source in AI answers?
- Appear in Google AI Overviews for specific queries?
- Compete with specific brands already getting cited?
- Optimize existing content or create new AI-optimized content?
4. Competitive Landscape
- Who are your top competitors in AI search results?
- Are they being cited where you're not?
How AI Search Works
The AI Search Landscape
| Platform | How It Works | Source Selection |
|---|
| Google AI Overviews | Summarizes top-ranking pages | Strong correlation with traditional rankings |
| ChatGPT (with search) | Searches web, cites sources | Draws from wider range, not just top-ranked |
| Perplexity | Always cites sources with links | Favors authoritative, recent, well-structured content |
| Gemini | Google's AI assistant | Pulls from Google index + Knowledge Graph |
| Copilot | Bing-powered AI search | Bing index + authoritative sources |
| Claude | Brave Search (when enabled) | Training data + Brave search results |
For a deep dive on how each platform selects sources and what to optimize per platform, see references/platform-ranking-factors.md.
Key Difference from Traditional SEO
Traditional SEO gets you ranked. AI SEO gets you cited.
In traditional search, you need to rank on page 1. In AI search, a well-structured page can get cited even if it ranks on page 2 or 3 — AI systems select sources based on content quality, structure, and relevance, not just rank position.
Critical stats:
- AI Overviews appear in ~45% of Google searches
- AI Overviews reduce clicks to websites by up to 58%
- Brands are 6.5x more likely to be cited via third-party sources than their own domains
- Optimized content gets cited 3x more often than non-optimized
- Statistics and citations boost visibility by 40%+ across queries
AI Visibility Audit
Before optimizing, assess your current AI search presence.
Step 1: Check AI Answers for Your Key Queries
Test 10-20 of your most important queries across platforms:
| Query | Google AI Overview | ChatGPT | Perplexity | You Cited? | Competitors Cited? |
|---|
| [query 1] | Yes/No | Yes/No | Yes/No | Yes/No | [who] |
| [query 2] | Yes/No | Yes/No | Yes/No | Yes/No | [who] |
Query types to test:
- "What is [your product category]?"
- "Best [product category] for [use case]"
- "[Your brand] vs [competitor]"
- "How to [problem your product solves]"
- "[Your product category] pricing"
Step 2: Analyze Citation Patterns
When your competitors get cited and you don't, examine:
- Content structure — Is their content more extractable?
- Authority signals — Do they have more citations, stats, expert quotes?
- Freshness — Is their content more recently updated?
- Schema markup — Do they have structured data you're missing?
- Third-party presence — Are they cited via Wikipedia, Reddit, review sites?
Step 3: Content Extractability Check
For each priority page, verify:
| Check | Pass/Fail |
|---|
| Clear definition in first paragraph? | |
| Self-contained answer blocks (work without surrounding context)? | |
| Statistics with sources cited? | |
| Comparison tables for "[X] vs [Y]" queries? | |
| FAQ section with natural-language questions? | |
| Schema markup (FAQ, HowTo, Article, Product)? | |
| Expert attribution (author name, credentials)? | |
| Recently updated (within 6 months)? | |
| Heading structure matches query patterns? | |
| AI bots allowed in robots.txt? | |
Step 4: AI Bot Access Check
Verify your robots.txt allows AI crawlers. Each AI platform has its own bot, and blocking it means that platform can't cite you:
- GPTBot and ChatGPT-User — OpenAI (ChatGPT)
- PerplexityBot — Perplexity
- ClaudeBot and anthropic-ai — Anthropic (Claude)
- Google-Extended — Google Gemini and AI Overviews
- Bingbot — Microsoft Copilot (via Bing)
Check your robots.txt for Disallow rules targeting any of these. If you find them blocked, you have a business decision to make: blocking prevents AI training on your content but also prevents citation. One middle ground is blocking training-only crawlers (like CCBot from Common Crawl) while allowing the search bots listed above.
See references/platform-ranking-factors.md for the full robots.txt configuration.
Optimization Strategy
The Three Pillars
1. Structure (make it extractable)
2. Authority (make it citable)
3. Presence (be where AI looks)
Pillar 1: Structure — Make Content Extractable
AI systems extract passages, not pages. Every key claim should work as a standalone statement.
Content block patterns:
- Definition blocks for "What is X?" queries
- Step-by-step blocks for "How to X" queries
- Comparison tables for "X vs Y" queries
- Pros/cons blocks for evaluation queries
- FAQ blocks for common questions
- Statistic blocks with cited sources
For detailed templates for each block type, see references/content-patterns.md.
Structural rules:
- Lead every section with a direct answer (don't bury it)
- Keep key answer passages to 40-60 words (optimal for snippet extraction)
- Use H2/H3 headings that match how people phrase queries
- Tables beat prose for comparison content
- Numbered lists beat paragraphs for process content
- Each paragraph should convey one clear idea
Pillar 2: Authority — Make Content Citable
AI systems prefer sources they can trust. Build citation-worthiness.
The Princeton GEO research (KDD 2024, studied across Perplexity.ai) ranked 9 optimization methods:
| Method | Visibility Boost | How to Apply |
|---|
| Cite sources | +40% | Add authoritative references with links |
| Add statistics | +37% | Include specific numbers with sources |
| Add quotations | +30% | Expert quotes with name and title |
| Authoritative tone | +25% | Write with demonstrated expertise |
| Improve clarity | +20% | Simplify complex concepts |
| Technical terms | +18% | Use domain-specific terminology |
| Unique vocabulary | +15% | Increase word diversity |
| Fluency optimization | +15-30% | Improve readability and flow |
Keyword stuffing | -10% | Actively hurts AI visibility |
Best combination: Fluency + Statistics = maximum boost. Low-ranking sites benefit even more — up to 115% visibility increase with citations.
Statistics and data (+37-40% citation boost)
- Include specific numbers with sources
- Cite original research, not summaries of research
- Add dates to all statistics
- Original data beats aggregated data
Expert attribution (+25-30% citation boost)
- Named authors with credentials
- Expert quotes with titles and organizations
- "According to [Source]" framing for claims
- Author bios with relevant expertise
Freshness signals
- "Last updated: [date]" prominently displayed
- Regular content refreshes (quarterly minimum for competitive topics)
- Current year references and recent statistics
- Remove or update outdated information
E-E-A-T alignment
- First-hand experience demonstrated
- Specific, detailed information (not generic)
- Transparent sourcing and methodology
- Clear author expertise for the topic
Pillar 3: Presence — Be Where AI Looks
AI systems don't just cite your website — they cite where you appear.
Third-party sources matter more than your own site:
- Wikipedia mentions (7.8% of all ChatGPT citations)
- Reddit discussions (1.8% of ChatGPT citations)
- Industry publications and guest posts
- Review sites (G2, Capterra, TrustRadius for B2B SaaS)
- YouTube (frequently cited by Google AI Overviews)
- Quora answers
Actions:
- Ensure your Wikipedia page is accurate and current
- Participate authentically in Reddit communities
- Get featured in industry roundups and comparison articles
- Maintain updated profiles on relevant review platforms
- Create YouTube content for key how-to queries
- Answer relevant Quora questions with depth
Machine-Readable Files for AI Agents
AI agents aren't just answering questions — they're becoming buyers. When an AI agent evaluates tools on behalf of a user, it needs structured, parseable information. If your pricing is locked in a JavaScript-rendered page or a "contact sales" wall, agents will skip you and recommend competitors whose information they can actually read.
Add these machine-readable files to your site root:
/pricing.md or /pricing.txt — Structured pricing data for AI agents
# Pricing — [Your Product Name]
## Free
- Price: $0/month
- Limits: 100 emails/month, 1 user
- Features: Basic templates, API access
## Pro
- Price: $29/month (billed annually) | $35/month (billed monthly)
- Limits: 10,000 emails/month, 5 users
- Features: Custom domains, analytics, priority support
## Enterprise
- Price: Custom — contact sales@example.com
- Limits: Unlimited emails, unlimited users
- Features: SSO, SLA, dedicated account manager
Why this matters now:
- AI agents increasingly compare products programmatically before a human ever visits your site
- Opaque pricing gets filtered out of AI-mediated buying journeys
- A simple markdown file is trivially parseable by any LLM — no rendering, no JavaScript, no login walls
- Same principle as
robots.txt (for crawlers), llms.txt (for AI context), and AGENTS.md (for agent capabilities)
Best practices:
- Use consistent units (monthly vs. annual, per-seat vs. flat)
- Include specific limits and thresholds, not just feature names
- List what's included at each tier, not just what's different
- Keep it updated — stale pricing is worse than no file
- Link to it from your sitemap and main pricing page
/llms.txt — Context file for AI systems (see llmstxt.org)
If you don't have one yet, add an llms.txt that gives AI systems a quick overview of what your product does, who it's for, and links to key pages (including your pricing).
Schema Markup for AI
Structured data helps AI systems understand your content. Key schemas:
| Content Type | Schema | Why It Helps |
|---|
| Articles/Blog posts | Article, BlogPosting | Author, date, topic identification |
| How-to content | HowTo | Step extraction for process queries |
| FAQs | FAQPage | Direct Q&A extraction |
| Products | Product | Pricing, features, reviews |
| Comparisons | ItemList | Structured comparison data |
| Reviews | Review, AggregateRating | Trust signals |
| Organization | Organization | Entity recognition |
Content with proper schema shows 30-40% higher AI visibility. For implementation, use the schema-markup skill.
Content Types That Get Cited Most
Not all content is equally citable. Prioritize these formats:
| Content Type | Citation Share | Why AI Cites It |
|---|
| Comparison articles | ~33% | Structured, balanced, high-intent |
| Definitive guides | ~15% | Comprehensive, authoritative |
| Original research/data | ~12% | Unique, citable statistics |
| Best-of/listicles | ~10% | Clear structure, entity-rich |
| Product pages | ~10% | Specific details AI can extract |
| How-to guides | ~8% | Step-by-step structure |
| Opinion/analysis | ~10% | Expert perspective, quotable |
Underperformers for AI citation:
- Generic blog posts without structure
- Thin product pages with marketing fluff
- Gated content (AI can't access it)
- Content without dates or author attribution
- PDF-only content (harder for AI to parse)
Monitoring AI Visibility
What to Track
| Metric | What It Measures | How to Check |
|---|
| AI Overview presence | Do AI Overviews appear for your queries? | Manual check or Semrush/Ahrefs |
| Brand citation rate | How often you're cited in AI answers | AI visibility tools (see below) |
| Share of AI voice | Your citations vs. competitors | Peec AI, Otterly, ZipTie |
| Citation sentiment | How AI describes your brand | Manual review + monitoring tools |
| Source attribution | Which of your pages get cited | Track referral traffic from AI sources |
AI Visibility Monitoring Tools
| Tool | Coverage | Best For |
|---|
| Otterly AI | ChatGPT, Perplexity, Google AI Overviews | Share of AI voice tracking |
| Peec AI | ChatGPT, Gemini, Perplexity, Claude, Copilot+ | Multi-platform monitoring at scale |
| ZipTie | Google AI Overviews, ChatGPT, Perplexity | Brand mention + sentiment tracking |
| LLMrefs | ChatGPT, Perplexity, AI Overviews, Gemini | SEO keyword → AI visibility mapping |
DIY Monitoring (No Tools)
Monthly manual check:
- Pick your top 20 queries
- Run each through ChatGPT, Perplexity, and Google
- Record: Are you cited? Who is? What page?
- Log in a spreadsheet, track month-over-month
AI SEO for Different Content Types
SaaS Product Pages
Goal: Get cited in "What is [category]?" and "Best [category]" queries.
Optimize:
- Clear product description in first paragraph (what it does, who it's for)
- Feature comparison tables (you vs. category, not just competitors)
- Specific metrics ("processes 10,000 transactions/sec" not "blazing fast")
- Customer count or social proof with numbers
- Pricing transparency (AI cites pages with visible pricing) — add a
/pricing.md file so AI agents can parse your plans without rendering your page (see "Machine-Readable Files" above)
- FAQ section addressing common buyer questions
Blog Content
Goal: Get cited as an authoritative source on topics in your space.
Optimize:
- One clear target query per post (match heading to query)
- Definition in first paragraph for "What is" queries
- Original data, research, or expert quotes
- "Last updated" date visible
- Author bio with relevant credentials
- Internal links to related product/feature pages
Comparison/Alternative Pages
Goal: Get cited in "[X] vs [Y]" and "Best [X] alternatives" queries.
Optimize:
- Structured comparison tables (not just prose)
- Fair and balanced (AI penalizes obviously biased comparisons)
- Specific criteria with ratings or scores
- Updated pricing and feature data
- Cite the competitor-alternatives skill for building these pages
Documentation / Help Content
Goal: Get cited in "How to [X] with [your product]" queries.
Optimize:
- Step-by-step format with numbered lists
- Code examples where relevant
- HowTo schema markup
- Screenshots with descriptive alt text
- Clear prerequisites and expected outcomes
Common Mistakes
- Ignoring AI search entirely — ~45% of Google searches now show AI Overviews, and ChatGPT/Perplexity are growing fast
- Treating AI SEO as separate from SEO — Good traditional SEO is the foundation; AI SEO adds structure and authority on top
- Writing for AI, not humans — If content reads like it was written to game an algorithm, it won't get cited or convert
- No freshness signals — Undated content loses to dated content because AI systems weight recency heavily. Show when content was last updated
- Gating all content — AI can't access gated content. Keep your most authoritative content open
- Ignoring third-party presence — You may get more AI citations from a Wikipedia mention than from your own blog
- No structured data — Schema markup gives AI systems structured context about your content
- Keyword stuffing — Unlike traditional SEO where it's just ineffective, keyword stuffing actively reduces AI visibility by 10% (Princeton GEO study)
- Hiding pricing behind "contact sales" or JS-rendered pages — AI agents evaluating your product on behalf of buyers can't parse what they can't read. Add a
/pricing.md file
- Blocking AI bots — If GPTBot, PerplexityBot, or ClaudeBot are blocked in robots.txt, those platforms can't cite you
- Generic content without data — "We're the best" won't get cited. "Our customers see 3x improvement in [metric]" will
- Forgetting to monitor — You can't improve what you don't measure. Check AI visibility monthly at minimum
Tool Integrations
For implementation, see the tools registry.
| Tool | Use For |
|---|
semrush | AI Overview tracking, keyword research, content gap analysis |
ahrefs | Backlink analysis, content explorer, AI Overview data |
gsc | Search Console performance data, query tracking |
ga4 | Referral traffic from AI sources |
Task-Specific Questions
- What are your top 10-20 most important queries?
- Have you checked if AI answers exist for those queries today?
- Do you have structured data (schema markup) on your site?
- What content types do you publish? (Blog, docs, comparisons, etc.)
- Are competitors being cited by AI where you're not?
- Do you have a Wikipedia page or presence on review sites?
Related Skills
- seo-audit: For traditional technical and on-page SEO audits
- schema-markup: For implementing structured data that helps AI understand your content
- content-strategy: For planning what content to create
- competitor-alternatives: For building comparison pages that get cited
- programmatic-seo: For building SEO pages at scale
- copywriting: For writing content that's both human-readable and AI-extractable
