wearevulcan.com
Weak AI visibility with 25 of 48 criteria passing. Biggest gap: llms.txt file.
Developer Tools & InfrastructureRobotics & HardwareVerdict
Below-average AEO readiness at 48/100 - multiple areas need attention. Key strengths include Internal Linking Structure, Sitemap Completeness, and RSS/Atom Feed. Priority gaps: llms.txt File, Content Licensing & AI Permissions, and Speakable Schema. 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.
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.
Minimize blocking scripts and stylesheets in <head> to improve content availability for AI crawlers.
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.
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.
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.
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.
Write concise, standalone answer paragraphs (2-3 sentences) immediately after question headings. These "snippet-ready" paragraphs are ideal for AI engine citations.
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.
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.
Rewrite multi-clause sentences into single-claim statements under 20 words. Pages with Flesch-Kincaid grade 16 outperform grade 19 in citation rates.
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.
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Score Breakdown
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