cube.dev
Moderate AI visibility with 32 of 48 criteria passing. Biggest gap: llms.txt file.
Verdict
Below-average AEO readiness at 54/100 - multiple areas need attention. Key strengths include Original Data & Expert Analysis, Semantic HTML5 & Accessibility, and Sitemap Completeness. Priority gaps: llms.txt File, Schema.org Structured Data, and RSS/Atom Feed. Topic coherence is moderate at 5/10, capping the score at 60. Tighter topical focus would lift this ceiling.
How to Improve
Add a machine-readable llms.txt file at your domain root that describes your site, services, and key pages for AI engines.
Create a comprehensive llms-full.txt with detailed page descriptions, content summaries, and topic taxonomy.
Trim oversized HTML, excessive DOM nodes, and large inline payloads that slow AI crawlers.
Update robots.txt to explicitly allow AI crawlers and include sitemap directive.
Implement hreflang tags and lang attributes so AI engines serve the correct language version when answering queries.
Ensure clean, well-structured HTML with proper meta tags, HTTPS, and parseable content for AI crawlers.
Optimize compression, cache headers, redirect chains, and HTML payload size for faster AI crawler access.
Minimize blocking scripts and stylesheets in <head> to improve content availability for AI crawlers.
Top Opportunities10
Ensure blog content consistently covers your core expertise areas rather than scattering across unrelated topics. AI engines build authority models - a site about "Medicare coverage" that also publishes about humidifiers and groceries dilutes its topical authority.
Expand articles to 1000+ words with structured H2/H3 sections, comparison tables, and expert analysis. Thin content (under 300 words) is rarely cited by AI engines. Deep, well-structured articles demonstrate expertise.
Create a dedicated FAQ page with FAQPage schema markup. Cover common questions about your products, services, and industry to become a direct answer source for AI engines.
Write 20-25 word self-contained answer sentences immediately after each H2 heading. 72.4% of AI-cited posts use this pattern - it gives engines a ready-made snippet to quote.
Define the primary entity in the first 500 characters, use consistent terminology (same term 70%+), and add "unlike X" signals to help AI engines distinguish your topics.
Implement JSON-LD structured data (Organization, Service, Product, FAQPage) on key pages. Schema markup helps AI engines extract and cite your content accurately.
Show direct use, testing, implementation, or lived experience with concrete observations, examples, screenshots, and lessons learned.
Add inline citations to external sources, "According to [Source]..." attribution phrases, and a Sources section at the end of key articles.
Rewrite multi-clause sentences into single-claim statements under 20 words. Pages with Flesch-Kincaid grade 16 outperform grade 19 in citation rates.
Add question-based headings (H2/H3) throughout your content. Use "What is...", "How does...", "Why should..." patterns that match how users query AI assistants.
Fix It With AI37
Score Breakdown
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