Ai Seo
Structure pages and articles so AI search engines and LLMs cite your product in answers, Overviews, and chat responses—not only traditional blue links.
Overview
AI SEO is an agent skill most often used in Launch (also Grow content, Validate landing) that helps solo builders optimize content to be cited by LLMs and AI search experiences.
Install
npx skills add https://github.com/coreyhaines31/marketingskills --skill ai-seoWhat is this skill?
- Maps triggers for AI SEO, AEO, GEO, LLMO, and zero-click visibility
- Optimizes for citations in ChatGPT, Perplexity, Claude, Gemini, Copilot, and Google AI Overviews
- Reads `.agents/product-marketing.md` (or legacy paths) before re-asking context
- Structured intake on current AI visibility, content assets, and competitive AI SERP behavior
- Explicit handoff: traditional technical SEO → seo-audit; structured data → schema skill
- Skill metadata version 2.0.1
Adoption & trust: 69.2k installs on skills.sh; 32.4k GitHub stars; 2/3 security scanners passed (skills.sh audits).
What problem does it solve?
Your site ranks modestly in Google but rarely appears as a source when buyers ask ChatGPT, Perplexity, or AI Overviews for recommendations in your category.
Who is it for?
Founders publishing docs, landing pages, and thought leadership who want LLM citations and AI Overview presence alongside traditional SEO.
Skip if: Pure technical crawl issues, Core Web Vitals-only projects, or teams that only need JSON-LD implementation without copy strategy—use seo-audit or schema instead.
When should I use this skill?
When the user wants AI SEO, AEO, GEO, LLMO, AI citations, AI visibility, zero-click search, or optimization for ChatGPT, Perplexity, Claude, or Gemini—not traditional technical SEO alone.
What do I get? / Deliverables
You leave with an AI-visibility-oriented content plan and on-page patterns aimed at extractable answers and citations, with clear follow-ups for schema or a classic seo-audit when needed.
- AI visibility context summary and gap analysis
- Actionable on-page and content recommendations for LLM citation
- Pointers to companion skills (seo-audit, schema) when scope exceeds AEO
Recommended Skills
Journey fit
Spans multiple journey phases - primary shelf plus alternate fits below.
Answer-engine and LLM visibility is a launch-era distribution problem once you have something to explain to the market. GEO/AEO is the sub-shelf for generative and answer-engine optimization distinct from classic technical SEO audits.
Where it fits
Rewrite hero and FAQ blocks so AI summarizers can quote definitive answers about your niche.
Prioritize pages and passages to target Perplexity and ChatGPT browsing citations at go-live.
Align classic SEO topics with AI Overview-friendly definitions and source-worthy stats.
Refresh blog posts with citable frameworks so assistants recommend your methodology.
Define what to monitor for LLM mentions and AI referral patterns alongside Search Console.
How it compares
Procedural AEO/GEO playbook inside the agent, not a replacement for a full technical SEO audit skill or an MCP analytics server.
Common Questions / FAQ
Who is ai-seo for?
Solo and indie builders with marketing skills in Claude Code or Cursor who ship content and want AI assistants to cite their product as a trustworthy source.
When should I use ai-seo?
At Launch when polishing site copy for GEO, in Grow when updating blog and docs for LLM retrieval, and in Validate when your landing page must answer buyer questions AI tools summarize.
Is ai-seo safe to install?
Treat it as marketing guidance that may read local context files; confirm permissions in your agent setup and review the Security Audits panel on this Prism page before enabling in production repos.
Workflow Chain
Then invoke: schema
SKILL.md
READMESKILL.md - Ai Seo
# 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.md` exists (or `.claude/product-marketing.md`, or the legacy `product-marketing-context.md` filename, 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](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 ### Google's Official Stance vs. Multi-Platform Reality This is important to read once before doing anything else. **Google's position** ([AI features optimization guide](ht