Moderate AI visibility with 30 of 53 criteria passing. Biggest gap: llms.txt file.
Verdict
Below-average AEO readiness at 50/100 - multiple areas need attention. Key strengths include Sitemap Completeness, RSS/Atom Feed, and Table & List Extractability. Priority gaps: llms.txt File, Q&A Content Format, and Speakable Schema. 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.
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.
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.
Trim oversized HTML, excessive DOM nodes, and large inline payloads that slow AI crawlers.
115/162 images lack explicit width/height - the most common cause of layout shift (CLS)
Implement hreflang tags and lang attributes so AI engines serve the correct language version when answering queries.
Top Opportunities10
View allEnsure 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.
Write concise, standalone answer paragraphs (2-3 sentences) immediately after question headings. These "snippet-ready" paragraphs are ideal for AI engine citations.
Add question-based headings (H2/H3) throughout your content. Use "What is...", "How does...", "Why should..." patterns that match how users query AI assistants.
Ensure every question-format heading (H2/H3) is followed by a direct answer paragraph. This pattern is ideal for AI engine snippet extraction.
Sections within pages contain identical or near-identical text. LLMs may flag this as low-quality or thin content, reducing citation authority. Rewrite duplicate blocks with unique angles.
Add specific numbers, percentages, statistics, and data points throughout your content. Fact-dense content gives AI engines concrete data to cite rather than vague claims.
Place a concise 40-80 word answer block in the first 300 words of each page. Avoid throat-clearing openers like "In this article..." and lead with the answer.
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.
Rewrite multi-clause sentences into single-claim statements under 20 words. Pages with Flesch-Kincaid grade 16 outperform grade 19 in citation rates.
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.