kilimcininkoroglu/ai-seo
claude/skills/ai-seo/SKILL.md
This skill MUST be invoked when the user says "ai seo", "seo analiz", "GEO audit", "site optimize", "AI arama optimizasyonu", "citability", "ai citation", "crawlers check", "llms.txt", "brand mentions", "structured data audit", "schema audit", "technical seo", "E-E-A-T", "ai visibility", "generative engine optimization", or any variation requesting website optimization for AI-powered search engines. Analyzes websites for AI search readiness across citability, crawler access, brand authority, structured data, technical foundations, and content quality.
$ install --global
skillsauthnpx skillsauth add kilimcininkoroglu/cli-tweaks ai-seoInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
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Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
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TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
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VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
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OSV-ScannerOpen Source Vulnerability database check
50%
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OWASP Dep-Check
50%
Last scanned: Apr 27, 2026, 12:46 PM28.1s9 files scanned
SKILL.md
- name:
- ai-seo
- description:
- >
- argument-hint:
- [audit | citability | crawlers | llmstxt | brands | schema | technical | content] <url>
AI SEO — Generative Engine Optimization
Optimize websites for AI-powered search engines (ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews) while maintaining traditional SEO foundations.
AI search is eating traditional search. This skill optimizes for where traffic is going, not where it was.
Usage
/ai-seo audit <url> # Full GEO + SEO audit with parallel analysis
/ai-seo citability <url> # AI citation readiness scoring
/ai-seo crawlers <url> # AI crawler access check (robots.txt)
/ai-seo llmstxt <url> # llms.txt analysis or generation
/ai-seo brands <url> # Brand mentions across AI-cited platforms
/ai-seo schema <url> # Structured data + entity recognition audit
/ai-seo technical <url> # Technical SEO foundations for AI
/ai-seo content <url> # Content quality + E-E-A-T assessment
Why GEO Matters
| Signal | Impact | |--------|--------| | AI-referred traffic growth | +527% YoY | | AI traffic conversion vs organic | 4.4x higher | | Brand mentions vs backlinks for AI | 3x stronger correlation | | Gartner: search traffic drop by 2028 | -50% | | Sites with llms.txt | < 5% (early mover advantage) |
Subcommands
| Subcommand | Command | Description |
|--------------|------------------------------|-------------------------------------------------|
| audit | /ai-seo audit <url> | Full GEO audit with composite scoring |
| citability | /ai-seo citability <url> | Passage-level AI citation readiness |
| crawlers | /ai-seo crawlers <url> | AI crawler access analysis (robots.txt) |
| llmstxt | /ai-seo llmstxt <url> | llms.txt standard analysis or generation |
| brands | /ai-seo brands <url> | Brand authority on AI training platforms |
| schema | /ai-seo schema <url> | Structured data + entity recognition |
| technical | /ai-seo technical <url> | Technical SEO for AI crawlers |
| content | /ai-seo content <url> | Content quality + E-E-A-T scoring |
- For
/ai-seo audit: see subcommands/audit.md - For
/ai-seo citability: see subcommands/citability.md - For
/ai-seo crawlers: see subcommands/crawlers.md - For
/ai-seo llmstxt: see subcommands/llmstxt.md - For
/ai-seo brands: see subcommands/brand-mentions.md - For
/ai-seo schema: see subcommands/schema.md - For
/ai-seo technical: see subcommands/technical.md - For
/ai-seo content: see subcommands/content.md
GEO Composite Score (Full Audit)
The full audit produces a weighted composite score (0-100):
| Category | Weight | Subcommand | |-----------------------------|--------|--------------| | AI Citability & Visibility | 25% | citability | | Brand Authority Signals | 20% | brands | | Content Quality & E-E-A-T | 20% | content | | Technical Foundations | 15% | technical | | Schema & Structured Data | 10% | schema | | Platform Optimization | 10% | crawlers + llmstxt |
Score interpretation:
| Range | Grade | Meaning | |-------|-------|---------| | 80-100 | A | AI-optimized — strong visibility in AI search | | 60-79 | B | Good foundation — targeted improvements needed | | 40-59 | C | Significant gaps — AI crawlers may struggle | | 20-39 | D | Major issues — minimal AI search presence | | 0-19 | F | Not optimized — invisible to AI search |
Business Type Detection
When running a full audit, detect the site type to adjust analysis focus:
| Type | Signals | Adjusted Focus | |------|---------|----------------| | SaaS | /pricing, /docs, /api, app subdomain | Documentation citability, API schema | | Local | Address, map embed, NAP data, reviews | LocalBusiness schema, Google Business | | E-commerce | /products, cart, price elements | Product schema, review markup | | Publisher | /blog, /articles, bylines, dates | Article schema, E-E-A-T, citability | | Agency | /services, /portfolio, /case-studies | Organization schema, brand authority |
How to Fetch Pages
All subcommands that need page content should use available tools:
- WebFetch for HTML content extraction and analysis
- Bash(curl -s) for raw file fetching (robots.txt, llms.txt, sitemaps)
- WebSearch for brand mention discovery across platforms
Do NOT use Python scripts or external dependencies. The LLM's analysis capabilities replace regex-based scoring with context-aware, more accurate assessment.
Output Format
All subcommands return analysis in the response as structured markdown. No files are created unless explicitly requested. Each analysis includes:
- Score (0-100) with grade (A-F)
- Key findings with specific file/line/URL references
- Prioritized recommendations (Critical → High → Medium → Low)
- Quick wins highlighted separately
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