seo-geo

Imported from sickn33/agentic-awesome-skills (skills/seo-geo/SKILL.md). Install upstream with npx skills add sickn33/agentic-awesome-skills --skill seo-geo. Copyright stays with the author.

AI Search / GEO Optimization (February 2026)

When to Use

• Use when improving visibility in AI Overviews, ChatGPT, Perplexity, or similar AI search systems.
• Use when evaluating llms.txt readiness, AI crawler access, or citation-oriented content structure.
• Use when the user asks about GEO, AI SEO, LLM visibility, or AI citations.

Evidence boundaries

Use a dated query/platform sample and actual citation/referral evidence. No market-share, correlation, passage-length or uplift figures are established by this file; correlations do not prove an optimization causes citations. Scores below are a disclosed qualitative rubric, not a provider ranking metric.

GEO Analysis Criteria (Updated)

1. Citability Score (25%)

Use self-contained passages sized for the topic; no universal optimal citation word count is established.

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%)

Evaluate citation sources on a defined current sample instead of assuming a universal ranking-position distribution.

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%)

Use relevant media when it helps the reader; measure any citation effect rather than promising a fixed uplift.

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
• 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%)

Crawler rendering capabilities differ. Inspect initial and rendered content for the actual target system; server-rendered critical content improves broad accessibility.

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:

Recommendation: Choose search and training access independently. OpenAI crawler guidance distinguishes OAI-SearchBot from GPTBot; do not enable training as a requirement for search visibility.

llms.txt Proposal

The llms.txt proposal provides agent-friendly navigation; its presence does not guarantee indexing or citations.

Location: /llms.txt (root of domain)

Format:

# Title of site
> Brief description

## Main sections
- `Page title -> https://example.com/page`: Description
- `Another page -> https://example.com/another-page`: 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)

Machine-readable licensing proposals are separate from search ranking or guaranteed crawler enforcement. Verify the current specification and publisher adoption before recommending an implementation; this guide does not establish legal enforceability or endorsements.

Platform-Specific Optimization

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 (self-contained, source-backed passages 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 concise 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
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

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.