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,' or 'zero-click search.' This skill covers content optimization for AI answer engines, monitoring AI visibility, and getting cited as a source. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema-markup.
npx skills add https://github.com/AvdLee/RocketSimApp --skill 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.
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):
| 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.
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:
Before optimizing, assess your current AI search presence.
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:
When your competitors get cited and you don't, examine:
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? | |
Verify your robots.txt allows AI crawlers. Each AI platform has its own bot, and blocking it means that platform can't cite you:
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.
1. Structure (make it extractable)
2. Authority (make it citable)
3. Presence (be where AI looks)
AI systems extract passages, not pages. Every key claim should work as a standalone statement.
Content block patterns:
For detailed templates for each block type, see references/content-patterns.md.
Structural rules:
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)
Expert attribution (+25-30% citation boost)
Freshness signals
E-E-A-T alignment
AI systems don't just cite your website — they cite where you appear.
Third-party sources matter more than your own site:
Actions:
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.
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:
| 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 |
| 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 |
Monthly manual check:
Goal: Get cited in "What is [category]?" and "Best [category]" queries.
Optimize:
Goal: Get cited as an authoritative source on topics in your space.
Optimize:
Goal: Get cited in "[X] vs [Y]" and "Best [X] alternatives" queries.
Optimize:
Goal: Get cited in "How to [X] with [your product]" queries.
Optimize:
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 |
A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).
Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working. Helps inspire and improve your own ad campaigns.
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Analyzes your recent Claude Code chat history to identify coding patterns, development gaps, and areas for improvement, curates relevant learning resources from HackerNews, and automatically sends a personalized growth report to your Slack DMs.
Complete App Store Optimization (ASO) toolkit for researching, optimizing, and tracking mobile app performance on Apple App Store and Google Play Store
NGS analysis toolkit. BAM to bigWig conversion, QC (correlation, PCA, fingerprints), heatmaps/profiles (TSS, peaks), for ChIP-seq, RNA-seq, ATAC-seq visualization.
Materials science toolkit. Crystal structures (CIF, POSCAR), phase diagrams, band structure, DOS, Materials Project integration, format conversion, for computational materials science.
Transforms vague UI ideas into polished, Stitch-optimized prompts. Enhances specificity, adds UI/UX keywords, injects design system context, and structures output for better generation results.
Take avdlee/ai-seo from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.