edufi.tech
Weak AI visibility with 28 of 48 criteria passing. Biggest gap: llms.txt file.
Verdict
Below-average AEO readiness at 47/100 - multiple areas need attention. Key strengths include Sitemap Completeness, RSS/Atom Feed, and Direct Answer Paragraphs. Priority gaps: llms.txt File, Content Licensing & AI Permissions, and Speakable Schema. Topic coherence is 3/10, which caps the overall score at 50. Focusing content on core expertise areas is the single highest-impact improvement.
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.
Minimize blocking scripts and stylesheets in <head> to improve content availability for AI crawlers.
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.
Trim oversized HTML, excessive DOM nodes, and large inline payloads that slow AI crawlers.
Implement hreflang tags and lang attributes so AI engines serve the correct language version when answering queries.
Optimize compression, cache headers, redirect chains, and HTML payload size for faster AI crawler access.
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.
Publish 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.
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.
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.
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.
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.
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.
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.
Fix It With AI42
Score Breakdown
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