ai-seo
When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers.
Skill by bhubbard
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/bhubbard-ai-seo
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: data, ml, security, writing
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/ai-seo
What's inside
- Skill 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,' 'optimize for Claude/Gemini,' 'llms.txt,' 'llms-full.txt,' 'OKF,' 'Open Knowledge Format,' 'knowledge bundle,' 'agent-readable site,' 'agent readiness,' 'is my site agent-ready,' 'WebMCP,' 'do listicles still work for AI,' 'ChatGPT stopped citing comparison pages,' or 'AI citation format shift.' 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.
- License
- MIT
- Metadata
- version: 2.5.0
- Instructions
- 483 lines in SKILL.md · view on GitHub
Files (10)
- SKILL.md
- evals.json · evals/
- agent-readiness.md · references/
- citations-vs-recommendations.md · references/
- content-patterns.md · references/
- content-types.md · references/
- format-volatility.md · references/
- okf.md · references/
- platform-ranking-factors.md · references/
- youtube-ai-citations.md · references/
SKILL.md (first lines)
# 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](https://developers.google.com/search/docs/fundamentals/ai-optimization-guide)): > "The best practices for SEO continue to be relevant because our generative AI features on Google Search are rooted in our core Search ranking and quality systems." Google explicitly says: - **No special markup or files are required** for AI Overviews or AI Mode - **Don't chunk content for AI** — write for people, organize with normal headings and paragraphs - **Don't write separate content for AI** — that risks "scaled content abuse" spam policy - **Helpful, reliable, people-first content** wins — same E-E-A-T standards as regular Search - **No AI-specific Search Console reporting** — use standard SEO metrics **Other AI engines (ChatGPT, Claude, Perplexity, Copilot) behave differently:** - They actively reward extractable structure — passages, FAQs, comparison tables, definition blocks - They parse `llms.txt`, structured pricing pages, and machine-readable files when present - They cite third-party sources (Reddit, Wikipedia, review sites) more heavily than top-ranked pages **What this means for the work:** - The structural patterns in this skill (40–60 word answer blocks, FAQ schema, comparison tables) help **non-Google AI engines** materially. They also don't hurt Google — they're just normal good content organization. - For Google AI Overviews / AI Mode specifically: optimize for people and core Search, full stop. Strong E-E-A-T, original information, semantic HTML, clean indexability. - For ChatGPT/Claude/Perplexity: layer on the extractable structure + llms.txt + machine-readable files. When in doubt, default to "write for people, organize for clarity" — that satisfies both camps. ### Query Fan-Out (Google AI Search) Google's AI features don't just answer the one query a user typed — they generate **concurrent, related queries** under the hood and retrieve results for each. Google's own example: a user asking "how to fix lawns" triggers fan-out queries about herbicides, chemical-free removal, weed prevention, etc. The AI synthesizes across all of them. **Implications:** - Single-page-per-keyword targeting is less effective. Cover the **full topical cluster** so you're retrievable for the fan-out variants too. - Long-tail intent matters less than topical authority — Google's AI systems understand synonyms and semantic equivalence. - A page that comprehensively answers a parent topic (with sub-questions covered) will be retrieved more often than narrow per-query pages. **Action**: when planning content, brainstorm the 5–10 related queries the AI is likely to fan out to and make sure your content (or your site as a whole) covers them. ChatGPT fans out too — and you can extract its *literal* background queries for your niche via DevTools (method in [references/format-volatility.md](references/format-volatility.md)). Post-5.6, ChatGPT's fan-outs shifted away from "best/vs/top" modifiers toward `site:` and "official" searches — use the extraction to see where your category's fan-outs stand today. --- ## 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]?"
From bhubbard/skills, MIT.
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Signals
- Stars
- 1
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Sep 26, 2026 (1 month ago)
- Last release
- Sep 26, 2026 (1 month ago)
From GitHub (fetched Oct 24, 2026).
Details
- Version
- 2.5.0
- License
- MIT
- Repository
- github.com/bhubbard/skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
ai-seo skill. Agent Mart. https://agentmart.dev/skills/bhubbard-ai-seo (last updated 2026-10-24)