Free tool
Schema Markup Grader.
Paste a URL and tell us what kind of page it is. We’ll crawl the live page, check its structured data, and show you exactly what’s there and what’s missing for AI Overviews, ChatGPT and rich results.
Grade a page.
Takes about 10 seconds
How this works: we fetch your live page and read its JSON-LD/schema.org markup directly — this is a real check against your actual page, not a mock result.
Why this matters more than it used to.
Structured data used to be a rich-results nicety — a star rating in a search snippet, a FAQ dropdown. Now it’s also one of the clearest signals you can give AI Overviews, ChatGPT and Perplexity about what a page actually is.
An LLM doesn’t read a page the way a person does. It leans on the machine-readable layer — JSON-LD schema.org markup — to confirm entity type, location, credentials, pricing and structure in one pass. A page that reads clearly to a human but only ships generic WebPage or Article markup is handing the model far less to work with than a competitor whose schema names exactly what the page is.
We see the same shape of gap across almost every audit: the content is right, the on-page schema is thin, and that gap quietly costs citations and rich results that a competitor with tighter markup picks up instead.
Get your real schema audit.
We’ll run a deeper pass across your actual page markup — every page type, every gap — and send back exactly what’s present, what’s missing, and what to fix first.
The schema check above is live. Your details go straight to Figment’s team. If that doesn’t work, your email app opens with everything pre-filled instead.
How to read your schema grade.
The grader fetches the page you enter and inspects the JSON-LD structured data it actually ships, rather than what a plugin claims to output. You get a type-by-type breakdown of what is present, what is missing for that kind of page, and which properties AI Overviews and rich results lean on most. Work through it in order. Fix type accuracy first: a service page marked up only as WebPage tells a model almost nothing, where a Service node with a named provider and areaServed tells it a great deal. Then fill the required properties, then the recommended ones that unlock rich results such as review stars, product pricing and breadcrumbs. Finally connect the entities, linking your Organization node to your pages so the whole site reads as one coherent thing rather than a pile of unrelated documents. Re-run the grader after each deploy to confirm the markup survived the build.
Two technical details account for most low grades. The first is duplicate, conflicting graphs: a theme, an SEO plugin and a booking widget each emitting their own Organization or LocalBusiness node, leaving a machine to guess which one is authoritative. Give each entity a stable @id and reference it instead of repeating it. The second is markup describing something the page does not visibly contain — review ratings or FAQ answers that exist only in the JSON-LD. Google treats that as a structured data violation, and it can cost you rich results altogether.
Related tools.
Schema rarely fails on its own. These two tools cover the context around it.
- GEO Readiness Checklist — structured data is one piece of AI-search readiness. The checklist scores the full 24-point picture, including direct-answer formatting, crawler access and corroboration, then ranks your weakest area.
- Local Pack Visibility Checker — if you are a local business, correct LocalBusiness markup only pays off if you are visible where customers search. This shows your live position in the Google local three-pack and names the businesses ahead of you.
