Weak AI visibility with 2 of 22 criteria passing. Biggest gap: llms.txt file.
Verdict
usemulligan.com shows low AEO readiness, with an overall score of 14 and multiple foundational machine-readability gaps. The site has crawlable HTTPS delivery and strong factual density (33 quantitative data points), but core discovery and interpretation signals are missing: no JSON-LD schema blocks, no `llms.txt` (404), no sitemap.xml (404), no RSS/Atom feed, and no canonical tag. Structural extraction is also weak on the homepage, with zero internal links, zero question headings, zero H1 tags, and no semantic navigation/footer landmarks. In its current state, AI engines can read text but cannot reliably map entities, page purpose, freshness, or content hierarchy.
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Guides for the criteria with the most room for improvement
Tidio has a 251-line llms.txt. Crisp has zero. The score gap: +29 points. This single file tells AI assistants exactly what your site does -and without it, they're guessing.
Tidio runs 4 JSON-LD schema types. Crisp runs zero. That's not a coincidence -it's the difference between a 63 and a 34. Structured data is the machine-readable layer AI trusts most.
AI assistants are question-answering machines. When your content is already shaped as questions and answers, you're handing AI a pre-formatted citation. Sites that do this right get extracted -sites that don't get skipped.
Our site runs 87 FAQ items across 9 categories with FAQPage schema on every one. That's not excessive -it's how we hit 88/100. Each Q&A pair is a citation opportunity AI can extract in seconds.
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