Weak AI visibility with 24 of 53 criteria passing. Biggest gap: llms.txt file.
Verdict
Critical AEO gaps at 41/100 - tinko.ru is largely invisible to AI engines. Key strengths include Sitemap Completeness, Direct Answer Paragraphs, and Canonical URL Strategy. Priority gaps: llms.txt File, RSS/Atom Feed, and Definition Patterns. 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.
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.
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.
Minimize blocking scripts and stylesheets in <head> to improve content availability for AI crawlers.
57/57 images lack explicit width/height - the most common cause of layout shift (CLS)
Top Opportunities10
View allExpand 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 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%.
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.
Add inline citations to external sources, "According to [Source]..." attribution phrases, and a Sources section at the end of key articles.
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.
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.
Add question-based headings (H2/H3) throughout your content. Use "What is...", "How does...", "Why should..." patterns that match how users query AI assistants.
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.
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.