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Seo Geo

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AgriciDaniel
seo-geo

Optimize content for AI Overviews (formerly SGE), ChatGPT web search, Perplexity, and other AI-powered search experiences. Generative Engine Optimization (GEO) analysis including brand mention signals, AI crawler accessibility, llms.txt compliance, passage-level citability scoring, and platform-specific optimization. Use when user says "AI Overviews", "SGE", "GEO", "AI search", "LLM optimization", "Perplexity", "AI citations", "ChatGPT search", or "AI visibility".

Overview

PublisherAgriciDaniel
Repositoryclaude-seo
Skill nameseo-geo
Stars
17.1K
Forks
2.5K
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by AgriciDaniel on GitHub. Read the source before you install it.

Installation

Install the Seo Geo AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/AgriciDaniel/claude-seo.git /tmp/claude-seo
mkdir -p .claude/skills
cp -r /tmp/claude-seo/skills/seo-geo .claude/skills/seo-geo
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Seo Geo in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Seo Geo on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Seo Geo is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

AI Search / GEO Optimization (May 2026)

Primary Source: Google's AI Optimization Guide

Google's official position, published under Search Central docs:

"Optimizing for generative AI search is still SEO from Google's perspective. AEO and GEO are rebranded labels for the same work."

Read references/google-ai-optimization-guide.md for the full synthesis, myth-busting list (llms.txt, chunking, AI-rephrasing, mention-farming, all rejected by Google as ineffective), and the Who/How/Why test for content quality.

Audits should frame GEO findings as SEO fundamentals applied to AI-search surfaces, not as a separate optimization discipline. When community recommendations contradict Google's primary source, defer to Google and note the contradiction in the report.

Key Statistics

MetricValueSource
AI Overviews reach2.5 billion+ monthly active users, reported from Google I/O 2026 keynote coverage; not confirmed on a Google-owned source; 200+ countriesThird-party I/O reporting
AI Overviews query coverage~50% of queries (third-party measurement; varies by country)Industry data
AI Mode monthly users1B+, reported from Google I/O 2026 keynote coverage; not confirmed on a Google-owned sourceThird-party I/O reporting
AI Mode modelcustom version of Gemini 2.5Google
AI-referred sessions growth527% (Jan-May 2025)SparkToro
ChatGPT weekly active users900 millionOpenAI
Perplexity monthly queries500+ millionPerplexity

Critical Insight: Brand Mentions > Backlinks

Brand mentions correlate 3x more strongly with AI visibility than backlinks. (Ahrefs December 2025 study of 75,000 brands)

SignalCorrelation with AI Citations
YouTube mentions~0.737 (strongest)
Reddit mentionsHigh
Wikipedia presenceHigh
LinkedIn presenceModerate
Domain Rating (backlinks)~0.266 (weak)

Only 11% of domains are cited by both ChatGPT and Google AI Overviews for the same query, so platform-specific optimization is essential.


GEO Analysis Criteria (Updated)

1. Citability Score (25%)

Optimal passage length: 134-167 words for AI citation. And ~44% of AI citations come from the first 30% of a page (SE Ranking study), front-load your most citable, self-contained answer rather than burying it below the fold.

Strong signals:

  • Clear, quotable sentences with specific facts/statistics
  • Self-contained answer blocks (can be extracted without context)
  • Direct answer in first 40-60 words of section
  • Claims attributed with specific sources
  • Definitions following "X is..." or "X refers to..." patterns
  • Unique data points not found elsewhere

Weak signals:

  • Vague, general statements
  • Opinion without evidence
  • Buried conclusions
  • No specific data points

2. Structural Readability (20%)

92% of AI Overview citations come from top-10 ranking pages, but 47% come from pages ranking below position 5, demonstrating different selection logic.

Strong signals:

  • Clean H1->H2->H3 heading hierarchy
  • Question-based headings (matches query patterns)
  • Short paragraphs (2-4 sentences)
  • Tables for comparative data
  • Ordered/unordered lists for step-by-step or multi-item content
  • FAQ sections with clear Q&A format

Weak signals:

  • Wall of text with no structure
  • Inconsistent heading hierarchy
  • No lists or tables
  • Information buried in paragraphs

3. Multi-Modal Content (15%)

Content with multi-modal elements sees 156% higher selection rates.

Check for:

  • Text + relevant images
  • Video content (embedded or linked)
  • Infographics and charts
  • Interactive elements (calculators, tools)
  • Structured data supporting media

4. Authority & Brand Signals (20%)

Strong signals:

  • Author byline with credentials
  • Publication date and last-updated date
  • Recency, content under 3 months old is ~3x more likely to be cited in AI answers; pages left stale 6+ months lose citation eligibility (SE Ranking, 1.3M-citation study). A scheduled refresh program is one of the highest-leverage GEO plays.
  • Citations to primary sources (studies, official docs, data)
  • Organization credentials and affiliations
  • Expert quotes with attribution
  • Entity presence in Wikipedia, Wikidata
  • Mentions on Reddit, YouTube, LinkedIn

Weak signals:

  • Anonymous authorship
  • No dates
  • No sources cited
  • No brand presence across platforms

5. Technical Accessibility (20%)

AI crawlers do NOT execute JavaScript. Server-side rendering is critical.

Check for:

  • Server-side rendering (SSR) vs client-only content
  • AI crawler access in robots.txt
  • llms.txt file presence and configuration
  • RSL 1.0 licensing terms

AI Crawler Detection

Check robots.txt for these AI crawlers:

CrawlerOwnerPurposeObeys robots.txt?
GPTBotOpenAIModel training only (NOT ChatGPT Search)yes
OAI-SearchBotOpenAIChatGPT Search citability (the crawler that decides it)yes
ChatGPT-UserOpenAIChatGPT browsing (user-triggered)no (user-triggered)
ClaudeBotAnthropicModel training only (NOT Claude's search features)yes
Claude-SearchBotAnthropicClaude/Claude.ai search-result citability (the crawler that decides it)yes
Claude-UserAnthropicClaude browsing on a user's behalf (user-triggered)no (user-triggered)
PerplexityBotPerplexityPerplexity AI searchyes
CCBotCommon CrawlTraining data (often blocked)yes
BytespiderByteDanceTikTok/Douyin AIyes
cohere-aiCohereCohere modelsyes
Google-ExtendedGoogleGemini/Vertex training & grounding only (NOT Google Search)yes
Google-CloudVertexBotGoogleSite-owner-requested Vertex AI Agent crawlsyes
Google-AgentGoogleAgentic browsing (Project Mariner), acts for a userno (user-triggered)
Google-NotebookLMGoogleFetches individual user-added source URLsno (user-triggered)
Google MessagesGoogleUser-triggered fetchno (user-triggered)
Applebot-ExtendedAppleApple Intelligence / generative-AI training data opt-out only (NOT Siri, Spotlight, or Safari search; does not itself crawl, it labels content already fetched by Applebot)yes

Sources: OpenAI crawlers, Google crawlers overview, Anthropic crawler support article, Apple Applebot-Extended support article. Anthropic's current crawler support article documents only ClaudeBot, Claude-User, and Claude-SearchBot; it does not list anthropic-ai, so the previously-unverified anthropic-ai row has been removed rather than kept as a guess.

Recommendation: Allow OAI-SearchBot, Claude-SearchBot, and PerplexityBot for AI search visibility. GPTBot, ClaudeBot, CCBot, and Applebot-Extended are training-only signals -- allow or block them on licensing preference, not on search-visibility grounds.

Check the right bot for the claim you are making

Two pairs are routinely conflated. Each claim below may only be supported by its own bot's robots.txt status -- check them separately and report them separately.

Claim you want to makeBot to checkBot that does NOT support this claim
"Content is citable in ChatGPT Search"OAI-SearchBotGPTBot
"Content is available for OpenAI model training"GPTBotOAI-SearchBot
"Content can be used for Gemini/Vertex training & grounding"Google-ExtendedGooglebot
"Content is eligible for Google Search / AI Overviews"GooglebotGoogle-Extended
"Content is citable in Claude's search features"Claude-SearchBotClaudeBot
"Content is available for Anthropic model training"ClaudeBotClaude-SearchBot
"Content can be used for Apple Intelligence training"Applebot-ExtendedApplebot
"Content is discoverable via Siri, Spotlight, or Safari search"ApplebotApplebot-Extended
  • Google-Extended governs Gemini and Vertex AI training and grounding use only. It does not affect inclusion in ordinary Google Search, or in AI Overviews and AI Mode, both of which are served from the Googlebot index. Never score Google-Extended as a "Google Search readiness" signal, and never cite a blocked Google-Extended as evidence that a site is missing from Google Search.
  • OAI-SearchBot is the crawler that determines ChatGPT Search citability. GPTBot is OpenAI's separate training crawler. Checking GPTBot access tells you nothing about whether ChatGPT Search can cite the page. A site that blocks GPTBot and allows OAI-SearchBot is fully citable in ChatGPT Search.
  • Claude-SearchBot is the crawler that determines citability in Claude's own search features. ClaudeBot is Anthropic's separate training crawler (per Anthropic's crawler support article). Checking ClaudeBot access tells you nothing about Claude search citability, and vice versa; report each separately.
  • Applebot-Extended is a training-data opt-out signal, not a crawler that fetches pages itself. Per Apple's support article, disallowing Applebot-Extended opts a site out of Apple Intelligence / generative-model training use, but the page remains discoverable through Siri, Spotlight, and Safari as long as Applebot itself is allowed. Never cite a blocked Applebot-Extended as evidence a site is missing from Apple's search surfaces.

Do not use these names interchangeably in report prose. When reporting crawler access, name the specific user-agent that was checked and the specific capability it governs.

User-triggered fetchers ignore robots.txt by design (Google-Agent, Google-NotebookLM, Google Messages, ChatGPT-User). robots.txt cannot block them, use server-side access controls. Google's canonical crawling/robots reference moved to developers.google.com/crawling (migrated 2025-11-20); IP-range files now live at /crawling/ipranges/ and googlebot.json was renamed common-crawlers.json. Emerging: Web Bot Auth (RFC 9421) lets bots authenticate via a Signature-Agent header + key directory (used by Google-Agent); reverse-DNS verification remains the fallback.


llms.txt Standard

Read references/llmstxt-evidence.md for the primary-source evidence (Mueller, Illyes, SE Ranking 300k-domain study, OtterlyAI server-log audit) on why /llms.txt is not currently a citation lever for major AI search systems. claude-seo reports presence but assigns no citation-ranking weight.

Google now states this explicitly. Google's AI optimization guide, introduced 2026-05-15 and clarified 2026-06-15, says llms.txt and other AI-text files are not needed for Google Search and do not help or hurt visibility or rankings. They may still serve non-Google systems. Never recommend llms.txt as a Google ranking or citation lever. Source: developers.google.com/search/docs/fundamentals/ai-optimization-guide

The emerging llms.txt standard provides AI crawlers with structured content guidance.

Location: /llms.txt (root of domain)

Format:

# Title of site
> Brief description

## Main sections
- [Page title](url): Description
- [Another page](url): Description

## Optional: Key facts
- Fact 1
- Fact 2

Check for:

  • Presence of /llms.txt
  • Structured content guidance
  • Key page highlights
  • Contact/authority information

RSL 1.0 (Really Simple Licensing)

New standard (December 2025) for machine-readable AI licensing terms.

Backed by: Reddit, Yahoo, Medium, Quora, Cloudflare, Akamai, Creative Commons

Check for: RSL implementation and appropriate licensing terms.


Platform-Specific Optimization

PlatformKey Citation SourcesOptimization Focus
Google AI OverviewsStrongly ranking-correlated, cites pages that already rank wellTraditional SEO + passage optimization
Google AI Mode (custom version of Gemini 2.5)Weakly ranking-correlated; broader pool (~9 domains cited/query, Ahrefs)Distinct surface: freshness, entity authority, citable passages beyond position 5
ChatGPTWikipedia (47.9%), Reddit (11.3%)Entity presence, authoritative sources
PerplexityReddit (46.7%), WikipediaCommunity validation, discussions
Bing CopilotBing index, authoritative sitesBing SEO, IndexNow

Two Google citation engines, not one. AI Mode and AI Overviews reach the same conclusion ~86% of the time but cite the same URLs only 13.7% of the time (Ahrefs study, 540K query pairs). Treat them as separate surfaces: ranking well in classic Search feeds AI Overviews, but AI Mode draws from a broader pool where freshness and entity authority outweigh raw position. Score both.

AI Mode is also a booking surface (2026-08-27). Flight price tracking with email alerts (180+ countries and territories), hotel booking through integrated partners, and fares shown in points or miles now happen inside AI Mode. Travel and hospitality clients should check partner eligibility; nothing here is a documented ranking change.

UX is now unified, surfaces still distinct. At Google I/O 2026 (2026-05-19) Google merged AI Overviews and AI Mode into "one seamless AI Search experience" (question → AI Overview → follow-up in AI Mode) with a new intelligent Search box. The experience is one flow, but the two citation engines remain technically distinct (different models/link sets), keep scoring both.

Citation surfaces & controls in AI Search (2026)

Google added many AI citation/source surfaces across AI Overviews and AI Mode (May 2026):

  • Preferred Sources, an eligible domain or subdomain can be selected by a user, making its content more likely to appear in that user's Top Stories and eligible for a preferred badge in AI Mode or AI Overviews. This is a per-user preference, not a documented general ranking signal. Publishers may offer Google's interactive button or a deeplink, but should not promise a site-wide ranking lift. Source: developers.google.com/search/docs/appearance/preferred-sources
  • "Highly Cited" badges, earned via original primary reporting that other articles cite.
  • Community Perspectives, elevates Reddit/forum/firsthand content.
  • Inline links, desktop hover Link Previews, and prominent link carousels.

Controlling AI-feature appearance: there is no AI-specific opt-out file. Appearance in AI Overviews and AI Mode is governed by standard preview/index directives, nosnippet, data-nosnippet, max-snippet, noindex (distinct from the third-party AI-crawler robots controls above). Source: developers.google.com/search/docs/appearance/ai-features

Search agents (live, not just WebMCP): Google's "Information Agents" run in the background to monitor topics, plus agentic booking/calling for select categories (rolling out to US users, summer 2026), so agent-friendly-page optimization (real interactive elements, accessibility tree, layout stability) now matters for actions, not only citations.


Output

Generate GEO-ANALYSIS.md with:

  1. GEO Readiness Score: XX/100
  2. Platform breakdown (Google AIO, ChatGPT, Perplexity scores)
  3. AI Crawler Access Status -- report each crawler separately with the capability it governs. Training access (GPTBot, Google-Extended, CCBot, ClaudeBot, Applebot-Extended) and search citability (OAI-SearchBot, Googlebot, PerplexityBot, Claude-SearchBot, Applebot) are distinct findings and must never be merged into one line.
  4. llms.txt Status (present, missing, recommendations)
  5. Brand Mention Analysis (presence on Wikipedia, Reddit, YouTube, LinkedIn)
  6. Passage-Level Citability (optimal 134-167 word blocks identified)
  7. Server-Side Rendering Check (JavaScript dependency analysis)
  8. Top 5 Highest-Impact Changes
  9. Schema Recommendations (for AI discoverability)
  10. Content Reformatting Suggestions (specific passages to rewrite)

Quick Wins

  1. Add "What is [topic]?" definition in first 60 words
  2. Create 134-167 word self-contained answer blocks
  3. Add question-based H2/H3 headings
  4. Include specific statistics with sources
  5. Add publication/update dates
  6. Implement Person schema for authors
  7. Allow key AI crawlers in robots.txt

Medium Effort

  1. Create /llms.txt file (optional: ignored by Google Search; may help other AI crawlers)
  2. Add author bio with credentials + Wikipedia/LinkedIn links
  3. Ensure server-side rendering for key content
  4. Build entity presence on Reddit, YouTube
  5. Add comparison tables with data
  6. Implement FAQ sections (structured, not schema for commercial sites)

High Impact

  1. Create original research/surveys (unique citability)
  2. Build Wikipedia presence for brand/key people
  3. Establish YouTube channel with content mentions
  4. Implement comprehensive entity linking (sameAs across platforms)
  5. Develop unique tools or calculators

DataForSEO Integration (Optional)

If DataForSEO MCP tools are available, use ai_optimization_chat_gpt_scraper to check what ChatGPT web search returns for target queries (real GEO visibility check) and ai_opt_llm_ment_search with ai_opt_llm_ment_top_domains for LLM mention tracking across AI platforms.

Error Handling

ScenarioAction
URL unreachable (DNS failure, connection refused)Report the error clearly. Do not guess site content. Suggest the user verify the URL and try again.
AI crawlers blocked by robots.txtReport exactly which crawlers are blocked and which are allowed. Provide specific robots.txt directives to add for enabling AI search visibility.
No llms.txt foundNote the absence (optional file; Google Search ignores it) and provide a ready-to-use llms.txt template for non-Google AI crawlers.
No structured data detectedReport the gap and provide specific schema recommendations (Article, Organization, Person) for improving AI discoverability.

FLOW Framework Integration

For prompt-guided AI content optimization, use /seo flow optimize <url>, FLOW's 21 optimize-stage prompts complement GEO's citability and structure analysis with evidence-led AI prompts.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Seo Geo AI skill do?

Optimize content for AI Overviews (formerly SGE), ChatGPT web search, Perplexity, and other AI-powered search experiences. Generative Engine Optimization (GEO) analysis including brand mention signals, AI crawler accessibility, llms.txt compliance, passage-level citability scoring, and platform-specific optimization. Use when user says "AI Overviews", "SGE", "GEO", "AI search", "LLM optimization", "Perplexity", "AI citations", "ChatGPT search", or "AI visibility".

Why use Seo Geo on TypingMind?

Because you install it once and use it with any model. Seo Geo is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Seo Geo in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AgriciDaniel/claude-seo/tree/main/skills/seo-geo. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Seo Geo?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Seo Geo?

As many as you like. As long as a model supports skills, you can use Seo Geo with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Seo Geo AI skill free?

Yes. It is published on GitHub by AgriciDaniel under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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