Structured data checker for AI search

Structured data tells AI search engines what your page is: an article, a product, a company, an FAQ. This checker validates your JSON-LD and flags markup that does not match the visible page.

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5 checks · 8% of the Slurp Score · Updated July 2026

Why structured data matters for AI search

Schema is a parsing aid rather than a ranking trick. Bing confirmed its LLMs read structured data for Copilot. Google says AI Overviews need no special markup, and one large study found no direct link between schema coverage and citation rates. GetSlurp weights it at 8%, which is what the evidence supports. It helps engines identify your brand and your content type.

Markup that lies is worse than no markup at all. A schema headline that does not match your H1 reads as manipulation, and so does a type describing content that is not on the page. GetSlurp verifies your JSON-LD parses, uses specific types instead of a bare WebPage, and matches what a visitor actually sees.

Studies and sources: Schema markup and AI citations, 2026 evidence review · Google structured data documentation

What GetSlurp checks

JSON-LD presence Whether structured data exists and parses cleanly.
Relevant types Article, Product, FAQPage or Organization rather than bare WebPage.
Schema and page match Whether your markup describes what visitors actually see.
FAQ markup Question and answer pairs engines can lift directly.
Breadcrumbs BreadcrumbList markup showing where the page sits.

Every check in this category

This list comes straight from the audit engine, so it always matches what the extension and MCP server actually run.

schema.jsonld-presentGraded

Structured data tells engines exactly what the page is, in a format they parse directly. Bing confirmed its LLMs read it, and it helps every engine identify your brand and content type.

Fix: Add JSON-LD structured data describing the page (Article, Product, Organization as appropriate).

schema.relevant-typesGraded

Generic WebPage markup says nothing; content-specific types (Article, Product, FAQPage...) are what machines can actually use.

Fix: Use the schema type that matches the page content instead of (or alongside) generic WebSite/WebPage.

schema.content-consistencyGraded

Schema that claims things the visible page does not say reads as manipulation and gets discounted.

Fix: Keep the schema headline aligned with the visible H1.

schema.faqGraded

FAQ-marked pages are cited disproportionately in several AI citation datasets; Q-and-A pairs are pre-chunked answers.

Fix: Where the page genuinely answers recurring questions, add an FAQ section with FAQPage schema.

schema.breadcrumbsGraded

BreadcrumbList tells machines where the page sits in the site, aiding entity and topic resolution.

Fix: Add BreadcrumbList schema matching the visible breadcrumb trail.

Structured data checker for AI search: frequently asked questions

Does schema markup help AI search?

It helps engines identify what your page is, and it reliably aids brand and content-type recognition. But it is not a ranking trick. Google says AI Overviews need no special markup, so GetSlurp treats schema as a parsing aid rather than a shortcut.

What schema types matter most for AI?

Specific types that match your content, like Article, Product, FAQPage or Organization, rather than a bare WebPage. The type should describe what a visitor actually sees on the page.

Can bad schema hurt my AI visibility?

Yes. Markup that lies is worse than none. A schema headline that does not match your H1, or a type describing content that is not on the page, reads as manipulation to an engine.

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