Weak AI visibility with 23 of 53 criteria passing. Biggest gap: llms.txt file.
Verdict
Critical AEO gaps at 41/100 - tcc.fl.edu is largely invisible to AI engines. Key strengths include Duplicate Content Blocks, Entity Density, and Indexability & Snippet Eligibility. Priority gaps: llms.txt File, Schema.org Structured Data, and RSS/Atom Feed. HTTPS is not enabled, which caps several criteria scores and reduces AI crawler trust. Topic coherence is moderate at 5/10, capping the score at 60. Tighter topical focus would lift this ceiling.
How to Improve
Ensure clean, well-structured HTML with proper meta tags, HTTPS, and parseable content for AI crawlers.
Update robots.txt to explicitly allow AI crawlers and include sitemap directive.
Generate a comprehensive sitemap with lastmod dates for all important pages.
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.
Add rel="canonical" tags to all pages to prevent duplicate content confusion.
Implement hreflang tags and lang attributes so AI engines serve the correct language version when answering queries.
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.
Optimize compression, cache headers, redirect chains, and HTML payload size for faster AI crawler access.
Top Opportunities10
View allPublish original research, statistics, case studies, or proprietary data that AI engines can cite. Unique data points make your content a primary source rather than a derivative one.
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.
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.
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.
Write concise, standalone answer paragraphs (2-3 sentences) immediately after question headings. These "snippet-ready" paragraphs are ideal for AI engine citations.
Ensure every question-format heading (H2/H3) is followed by a direct answer paragraph. This pattern is ideal for AI engine snippet extraction.
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.
Use HTML tables for comparison data and ordered/unordered lists for features, steps, and specifications. Structured data formats are directly extractable by AI engines for answers.
Add question-based headings (H2/H3) throughout your content. Use "What is...", "How does...", "Why should..." patterns that match how users query AI assistants.
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.