Optimize content for AI Overviews (formerly SGE), ChatGPT web search, Perplexity, and other AI-powered search experiences.

MITAuto-check passedMarketing & SEO

Install SEO Geo

skills CLI
$ npx skills add hashgraph-online/awesome-codex-plugins --skill seo-geo -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install hashgraph-online/awesome-codex-plugins seo-geo --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/avalonreset/seo-dungeon/skills/seo-geo .claude/skills/seo-geo && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
seo-geo
GitHub stars
1.3k
Token cost
~3.7k tokens
SKILL.md length
1,719 words
Files
4 (incl. references)
Skills in repo
716
Repo updated
First seen
Licence
MIT

At a glance

Optimize content for AI Overviews (formerly SGE), ChatGPT web search, Perplexity, and other AI-powered search experiences.

  • Works in 5 steps: Citability Score (25%) → Structural Readability (20%) → Multi-Modal Content (15%) → …
  • User says AI Overviews
  • SKILL.md covers Primary Source: Google's AI…, Key Statistics, Critical Insight: Brand… and GEO Analysis Criteria (Updated), plus 11 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

SEO Geo is an agent skill from hashgraph-online/awesome-codex-plugins. 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 presence (optional; ignored by Google Search), 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".

Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/google-ai-optimization-guide.md` and `references/llmstxt-evidence.md`).

It sits in Marketing & SEO, covering AI search optimization and Web search. It works with OpenAI and Perplexity. The repository describes itself as: A curated list of awesome OpenAI Codex / ChatGPT plugins, skills, and resources. The 1 Codex Marketplace. See live plugins at: https://hol.org/plugins/best-codex-plugins. The licence is MIT.

When your agent uses it

  • User says AI Overviews
  • LLM optimization

Example prompts

  • “AI Overviews”
  • “AI search”
  • “LLM optimization”
  • “/seo-geo”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Citability Score (25%)
  2. Structural Readability (20%)
  3. Multi-Modal Content (15%)
  4. Authority & Brand Signals (20%)
  5. Technical Accessibility (20%)

What it can do on your machine

Read from SKILL.md and the folder at commit 3e1456a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

SEO Geo loads about 3.7k tokens when it runs, and up to ~6.1k if it reads all its reference files. Until then it costs about 128 tokens; SKILL.md has 1,719 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~128
When it runs · the whole SKILL.md, loaded when a task matches
~3.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from hashgraph-online/awesome-codex-plugins at commit 3e1456a, republished under its MIT licence (© hashgraph-online). 1,719 words, ~3,699 tokens.

Download SKILL.mdSave it as .claude/skills/seo-geo/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
seo-geo
description
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 presence (optional; ignored by Google Search), 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".
user-invocable
true
argument-hint
[url]
license
MIT
metadata.author
AgriciDaniel
metadata.version
2.2.5
metadata.category
seo

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

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?
GPTBotOpenAIChatGPT web searchyes
OAI-SearchBotOpenAIOpenAI search featuresyes
ChatGPT-UserOpenAIChatGPT browsing (user-triggered)no (user-triggered)
ClaudeBotAnthropicClaude web featuresyes
PerplexityBotPerplexityPerplexity AI searchyes
CCBotCommon CrawlTraining data (often blocked)yes
anthropic-aiAnthropicClaude trainingyes
BytespiderByteDanceTikTok/Douyin AIyes
cohere-aiCohereCohere modelsyes
Google-ExtendedGoogleGemini/Vertex training & grounding opt-outyes
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)

Recommendation: Allow GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot for AI search visibility. Block CCBot and training crawlers if desired.

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.


Show full SKILL.md (765 more words)Show less

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.

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 (which crawlers allowed/blocked)
  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 credentials or optional tools are available, use direct DataForSEO calls to check what ChatGPT web search returns for target queries (real GEO visibility check) and to run 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.

© hashgraph-online, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references) in plugins/avalonreset/seo-dungeon/skills/seo-geo of hashgraph-online/awesome-codex-plugins.

  • SKILL.md
  • LICENSE.txt
  • references/google-ai-optimization-guide.md
  • references/llmstxt-evidence.md

Open the folder on GitHubat commit 3e1456a

Compare with similar skills

SEO Geo next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

SEO Geo compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
SEO Geo this skillhashgraph-online/awesome-codex-plugins1.3k—~3.7kAutomated safety check: PassMIT
Geo Fundamentalswasp-lang/wasp19k9 repos~861Automated safety check: PassMIT
Marketing OsYuzzyuk/marketing-os540—~2.5kAutomated safety check: PassMIT
Geoliangdabiao/GEO-Content-Optimizer-Skill2051 repos~2.3kAutomated safety check: NotesMIT
Geo Optimizerliangdabiao/GEO-Content-Optimizer-Skill205—~1.1kAutomated safety check: PassNone
SEO Auditshadcn-labs/agentcn490—~598Automated safety check: PassMIT

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Categories

Questions about SEO Geo

What does SEO Geo do?

Optimize content for AI Overviews (formerly SGE), ChatGPT web search, Perplexity, and other AI-powered search experiences. SEO Geo is an agent skill from hashgraph-online/awesome-codex-plugins. Optimize content for AI Overviews (formerly SGE), ChatGPT web search, Perplexity, and other AI-powered search experiences.

When should I use SEO Geo?

SEO Geo fits situations like: user says AI Overviews; LLM optimization.

How do I install SEO Geo in Claude Code?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill seo-geo -a claude-code`. Or copy the skill folder (plugins/avalonreset/seo-dungeon/skills/seo-geo in hashgraph-online/awesome-codex-plugins) into .claude/skills/seo-geo in your project. Claude Code loads it when a task matches its description.

How do I install SEO Geo in Codex?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill seo-geo -a codex`. Or copy the skill folder (plugins/avalonreset/seo-dungeon/skills/seo-geo in hashgraph-online/awesome-codex-plugins) into .agents/skills/seo-geo in your project. Codex loads it when a task matches its description.

Can I use SEO Geo in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add hashgraph-online/awesome-codex-plugins --skill seo-geo -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/seo-geo, .gemini/skills/seo-geo, .github/skills/seo-geo and .opencode/skills/seo-geo in your project.

What does SEO Geo need to run?

SKILL.md names no scripts, command-line tools or credentials: SEO Geo is instructions for the agent only.

Does SEO Geo access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is SEO Geo safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does SEO Geo use?

SEO Geo is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does SEO Geo use?

About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.4k tokens, read only when the agent opens those files.

What are the alternatives to SEO Geo?

Skills that share tags, products or a category with SEO Geo: Geo Fundamentals (wasp-lang/wasp, 19k stars), Marketing Os (Yuzzyuk/marketing-os, 540 stars), Geo (liangdabiao/GEO-Content-Optimizer-Skill, 205 stars) and Geo Optimizer (liangdabiao/GEO-Content-Optimizer-Skill, 205 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains SEO Geo?

hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,267 GitHub stars. The repository holds 716 skills in this directory. The repository was last updated on October 10, 2026.

Source: hashgraph-online/awesome-codex-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.