localmilkrun.com
Weak AI visibility with 24 of 48 criteria passing. Biggest gap: llms.txt file.
Verdict
Below-average AEO readiness at 47/100 - multiple areas need attention. Key strengths include Canonical URL Strategy, Duplicate Content Blocks, and Cross-Page Duplicate Content. Priority gaps: llms.txt File, Content Freshness Signals, and Sitemap Completeness. 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.
Generate a comprehensive sitemap with lastmod dates for all important pages.
Minimize blocking scripts and stylesheets in <head> to improve content availability 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.
Ensure clean, well-structured HTML with proper meta tags, HTTPS, and parseable content for AI crawlers.
Top Opportunities10
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.
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.
Ensure every question-format heading (H2/H3) is followed by a direct answer paragraph. This pattern is ideal for AI engine snippet extraction.
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.
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.
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 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%.
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.
Fix It With AI44
Score Breakdown
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