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WebVello
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Schema Markup Validator

Enter any URL and we'll fetch the live page, parse every JSON-LD block in its HTML, and show you exactly what search engines see — including what's broken.

We fetch the live page server-side and parse every JSON-LD block in its HTML. Nothing is stored.

What This Validator Checks

Three layers of validation, run against the page search engines actually fetch.

JSON parse errors

A single stray comma silently kills an entire schema block. We surface the exact parse error and the offending source.

Required fields per type

Articles need headlines, FAQ pages need questions, products need names — we flag gaps against Google's documented requirements for 19 common types.

Entity graph coherence

Duplicate @id nodes and references to entities that are never defined — the failures paste-in validators can't see because they only look at one block.

What crawlers actually receive

We validate the served HTML, not your source code. If a deploy dropped your schema or JavaScript injects it too late, this is where you find out.

Why Validate Against the Live Page?

Most schema problems we find in audits aren't authoring mistakes — they're deployment mistakes. The markup was written correctly, then a template change dropped it, a build stripped it, or it was moved into JavaScript that runs after crawlers read the HTML. A paste-in validator says everything is fine because the snippet you paste is fine. The page is not.

Structured data is also how AI search systems — Google AI Overviews, ChatGPT, Perplexity — resolve who you are: your organization, services, and content as connected entities. A broken entity graph doesn't just cost rich results; it weakens the machine-readable identity those systems cite. That's why this tool checks @id references across every block on the page, not blocks in isolation.

If the validator surfaces problems you'd rather not fix alone, schema and entity architecture is core to our AI SEO and generative engine optimization work — see our methodology for how we verify every change.

How common are these failures? We ran this exact engine across 81 marketing agencies from our published rankings — read the study: 14% shipped no JSON-LD at all, and 13% of those with schema had entity-graph flaws.

Frequently Asked Questions

How the validator works, what it can and can't see, and why JSON-LD matters for AI search.

It fetches your live page server-side, extracts every <script type="application/ld+json"> block from the HTML, and checks three layers: does the JSON parse, are the fields Google documents as required for each type present (e.g. headline for Article, mainEntity for FAQPage), and is the entity graph coherent — duplicate @id values and references to entities that are never defined.
Paste-in validators check the snippet you give them. This tool checks what search engines actually receive when they fetch your URL — which catches a whole class of real-world failures: schema that never made it into the deployed page, blocks broken by a templating bug, or markup that only exists after client-side JavaScript runs.
The most common reason is that your schema is injected by client-side JavaScript after page load. This tool reads the static HTML response, which is also what many crawlers see first. Google can usually render JavaScript, but server-rendered JSON-LD removes that dependency entirely and is the pattern we recommend.
JSON-LD is the schema.org format Google recommends for structured data: a script block that describes your page's entities — organization, services, articles, FAQs — in machine-readable form. Search engines use it for rich results, and AI search systems use the same entity data to understand who you are and when to cite you.
An @id gives an entity a stable address so other blocks can reference it instead of redefining it — for example, every page pointing to one canonical Organization node. Duplicate @ids with different content confuse that graph, and references to @ids that are never defined anywhere leave crawlers with dangling pointers.
No. The page is fetched, parsed in memory, and the analysis is returned to you. We keep no copy of your HTML or your structured data.

Want Your Entity Graph Built Right?

We build schema architectures that connect every page to one coherent organization graph — the foundation for rich results and AI citations.

Talk to Us About Structured Data
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