clipr.ai
Weak AI visibility with 27 of 48 criteria passing. Biggest gap: llms.txt file.
Verdict
Below-average AEO readiness at 49/100 - multiple areas need attention. Key strengths include Schema.org Structured Data, Q&A Content Format, and Comprehensive FAQ Section. Priority gaps: llms.txt File, Sitemap Completeness, and RSS/Atom Feed. Topic coherence is 4/10, which caps the overall score at 55. 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.
Generate a comprehensive sitemap with lastmod dates for all important pages.
Update robots.txt to explicitly allow AI crawlers and include sitemap directive.
Minimize blocking scripts and stylesheets in <head> to improve content availability for AI crawlers.
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.
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
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.
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.
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.
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.
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.
Show direct use, testing, implementation, or lived experience with concrete observations, examples, screenshots, and lessons learned.
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.
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Guides for the criteria with the most room for improvement