Structured data validity

What this check looks for

For pages with structured data present, this check runs each JSON-LD block through schema validation and counts blocks with one or more errors. Any invalid block fails, quoting its type and a truncated summary of the specific validation errors. A page with no structured data reports "na" (there's nothing to validate); a page where every block validates cleanly passes.

Why it matters

Invalid structured data is often worse than none at all: search engines that attempt to parse a broken or incomplete JSON-LD block for a rich-result feature (star ratings, product pricing, FAQ snippets) will simply reject it and fall back to plain text, meaning you've done the work of adding markup without getting any of its benefit. Validation errors — a missing required property, a malformed date, an incorrect nested type — are easy to introduce when markup is hand-written or a template changes without updating every field. AI systems parsing JSON-LD as a trust signal treat malformed schema similarly to missing schema, since a block they can't reliably parse gives them nothing usable to cite.

How to fix it

Fix the specific validation errors reported, checking that every required property for the type is present and correctly typed:

<!-- Missing required "name" and malformed date -->
<script type="application/ld+json">
{"@context":"https://schema.org","@type":"Article","datePublished":"July 19"}
</script>

<!-- Fixed: required properties present, date in ISO 8601 -->
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "How Noise Cancellation Works",
  "datePublished": "2026-07-19"
}
</script>

Run any structured data through Google's Rich Results Test or the Schema.org validator after changes to catch errors before they ship.