Seo GeoSAFE

Universal SEO skill for Claude Code. 26 sub-skills + 19 sub-agents covering technical SEO, E-E-A-T, schema, GEO/AEO, agent readiness (Lighthouse Agentic Browsing, WebMCP, llms.txt), backlinks, local SEO, e-commerce, international SEO, Google APIs, and PDF/Excel reporting. 9 optional extensions for l

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: seo-geo
description: >
  Audit and improve content for AI Overviews and answer engines, including
  citability, entity clarity, crawler access, brand signals, and passage
  structure.
user-invocable: true
argument-hint: "[url]"
license: MIT
metadata:
  author: AgriciDaniel
  version: "2.4.2"
  category: seo
---

# AI Search / GEO Optimization (May 2026)

## Primary Source: Google's AI Optimization Guide

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

> "From Google Search's perspective, optimizing for generative AI search is
> optimizing for the search experience, and thus **still SEO**."

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

Third-party figures below were not re-verified on 2026-09-23. Quote them only
with their source and date, or leave them out.

| Metric | Value | Source |
|--------|-------|--------|
| AI Overviews reach | 2.5 billion+ monthly active users, reported from Google I/O 2026 keynote coverage; not confirmed on a Google-owned source; 200+ countries | Third-party I/O reporting |
| AI Overviews query coverage | ~50% of queries (third-party measurement; varies by country) | Industry data |
| AI Mode monthly users | 1B+ (Google, I/O 2026, 2026-05-19) | Google (blog.google) |
| AI Mode model | Google upgrades it often (Gemini 3.5 Flash became the default on 2026-05-19, and newer Flash models have shipped since); never tie advice to a model | Google (blog.google) |
| AI-referred sessions growth | 527% (Jan-May 2025) | Third-party (attributed to SparkToro; not re-verified) |
| ChatGPT weekly active users | 1 billion+ (reported August 2026; 900 million in February 2026) | OpenAI, via press reporting |
| Perplexity monthly queries | 500+ million | Perplexity |

## Critical Insight: Brand Mentions > Backlinks

**Brand mentions correlate 3x more strongly with AI visibility than backlinks.**
(Ahrefs study of 75,000 brands, published 2025-12-12; it follows Ahrefs' May 2025 AI Overviews study)

| Signal | Correlation with AI Citations |
|--------|------------------------------|
| YouTube mentions | ~0.737 (strongest) |
| Reddit mentions | High |
| Wikipedia presence | High |
| LinkedIn presence | Moderate |
| 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%)

**Self-contained answer blocks** are easy for AI systems to quote. Third-party
studies suggest roughly 130-170 words; this is a readability heuristic, not a
Google requirement (Google's AI optimization guide says you do not need to chunk
content for AI). 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%)

Multi-modal content can support selection in AI answers (third-party claims only; no primary source gives a figure).

**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%)

**Many AI crawlers fetch raw HTML without running JavaScript** (for example GPTBot and PerplexityBot in public tests), while Googlebot renders JavaScript and feeds AI Overviews and AI Mode. Server-side rendering keeps content visible to all of them.

**Check for:**
- Server-side rendering (SSR) vs client-only content
- AI crawler access in robots.txt
- llms.txt presence (reported for completeness; it carries **no weight** in this score, see `references/llmstxt-evidence.md`)
- RSL 1.0 licensing terms

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

What the source does

Filesystem

none-observed

Network

none-observed

Shell

none-observed

Dependencies

pinned

Secrets in source

none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.