meadowburke.com
Weak AI visibility with 29 of 53 criteria passing. Biggest gap: llms.txt file.
Verdict
Below-average AEO readiness at 48/100 - multiple areas need attention. Key strengths include Sitemap Completeness, Fact & Data Density, and Content Publishing Velocity. Priority gaps: llms.txt File, Comprehensive FAQ Section, and Content Licensing & AI Permissions. 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.
Add rel="canonical" tags to all pages to prevent duplicate content confusion.
Ensure clean, well-structured HTML with proper meta tags, HTTPS, and parseable content for AI crawlers.
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.
120/156 images lack explicit width/height - the most common cause of layout shift (CLS)
Optimize compression, cache headers, redirect chains, and HTML payload size for faster AI crawler access.
Trim oversized HTML, excessive DOM nodes, and large inline payloads that slow 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.
Add question-based headings (H2/H3) throughout your content. Use "What is...", "How does...", "Why should..." patterns that match how users query AI assistants.
Add inline citations to external sources, "According to [Source]..." attribution phrases, and a Sources section at the end of key articles.
Create a dedicated FAQ page with FAQPage schema markup. Cover common questions about your products, services, and industry to become a direct answer source for AI engines.
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.
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.
Write self-contained definition sentences and single-claim statements that AI engines can quote directly. Avoid pronouns like "this" or "that" at the start of answer paragraphs.
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 AI45
Score Breakdown
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