arcube.org
Moderate AI visibility with 30 of 48 criteria passing. Biggest gap: llms.txt file.
Verdict
Below-average AEO readiness at 54/100 - multiple areas need attention. Key strengths include Schema.org Structured Data, Direct Answer Paragraphs, and Fact & Data Density. Priority gaps: llms.txt File, RSS/Atom Feed, and Speakable Schema.
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.
Update robots.txt to explicitly allow AI crawlers and include sitemap directive.
Ensure clean, well-structured HTML with proper meta tags, HTTPS, and parseable content for AI crawlers.
Trim oversized HTML, excessive DOM nodes, and large inline payloads that slow AI crawlers.
Generate a comprehensive sitemap with lastmod dates for all important pages.
Optimize compression, cache headers, redirect chains, and HTML payload size for faster AI crawler access.
Add rel="canonical" tags to all pages to prevent duplicate content confusion.
Minimize blocking scripts and stylesheets in <head> to improve content availability for AI crawlers.
Implement hreflang tags and lang attributes so AI engines serve the correct language version when answering queries.
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.
The same paragraphs appear on multiple pages. AI engines may only index one version and ignore the rest. Rewrite shared content so each page offers a unique perspective.
Include "our analysis", "our data", "our testing" phrases backed by original research or proprietary data. 52.2% of AI-cited posts contain owned data signals.
Include dateModified schema, visible last-updated dates, and time elements on content pages. Fresh content signals help AI engines prioritize your pages over stale alternatives.
Add more proper nouns throughout content - named sources, organizations, tools, studies, and locations. Cited text averages 20.6% proper nouns; most sites fall well below 15%.
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.
Add inline citations to external sources, "According to [Source]..." attribution phrases, and a Sources section at the end of key articles.
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.
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.
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 AI43
Score Breakdown
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