What schemas does your page expose?

How it works

You give us a URL. We fetch the page on our server using a hardened fetcher that rejects private IPs, loopback addresses, and redirect chains pointed at internal networks. Same protections the AI Readiness Checker uses, same SSRF posture — the inspector cannot be tricked into scanning your internal admin panel.

From the returned HTML we extract every <script type="application/ld+json"> block, parse each one independently (so a single broken block does not abort the whole scan), then walk the parsed JSON recursively to collect every @type — including types nested inside @graph, mainEntity, author, publisher, and other entity references. Most generic validators only look at the top-level type and miss the rest.

The AI-citation score is opinionated, not a generic schema audit. We weight types by how AI answer-engines actually use them. Article and BlogPosting are worth the most because they ground citations with author and date context. FAQPage entries get lifted into AI answers verbatim. Organization grounds your brand in knowledge graphs. BreadcrumbList tells AI your site hierarchy. Equivalent types in the same group only count once, so layering Article + BlogPosting on the same page does not double-score.

This is a starting point, not a finished audit. Adding missing schemas is necessary but not sufficient — the underlying content still has to deserve the citation. Use this tool to find gaps, then write the content that fills them.