AI-Readiness

What it checks

AI-Readiness inspects the publicly visible signals an answer engine relies on, grouped into pillars:

• Discoverability: crawlability, robots rules, whether AI crawlers are allowed, sitemap, and the emerging llms.txt standard.
• Structured data: schema.org markup that lets engines parse entities, offers, and relationships.
• Metadata: titles, descriptions, and social/preview tags.
• Content structure: headings, semantics, and how cleanly the page reads without a browser.
• Answerability: value-proposition clarity, quotability, citation-worthiness, and clear entity naming.

How the scan works

Deterministic checks read the page's HTML, headers, and crawl files directly. A language model adds a qualitative layer over answerability, content structure, structured data, metadata, and discoverability, and every finding it raises names the AI-consumption consequence rather than generic marketing advice. The crawler identifies as the major AI crawlers so the result reflects what those engines actually see.

The score and findings

A run returns a 0-100 score and findings ranked by severity (critical, high, medium, low, info). The score reflects how ready the page is for AI search and citation; each finding carries its category, the affected URL, the evidence, and a recommended fix. Completed runs are immutable, so you can compare scores across runs to see whether a change moved the needle.

Free vs paid

• Free: one AI-Readiness homepage result each month.
• Paid plans: audit any single page on your domain, one URL per run, plus history and the other audit products.

See Pricing for plan details, or read the Quickstart to run your first audit.