Enter a page URL to check whether its JSON-LD is present in the raw HTML, parses correctly, forms a consistent entity graph, and agrees with the visible page. Each issue includes the evidence behind it.
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The checker reads the raw HTML without running JavaScript. This shows whether the markup is available before client-side rendering. Use it alongside Schema Markup Validator for vocabulary checks and Rich Results Test for Google feature eligibility.
Schema check results
JSON-LD found in the raw HTML
Review the exact markup used for this check. Valid JSON is formatted for readability; invalid blocks are shown as received so you can locate the parsing problem.
The four rungs
How to read the verdicts
✅ No issue was found in the checks this tool can run.
⚠️ Review the finding and confirm it manually.
❌ A specific issue was found. The evidence appears beside it.
N/A The page does not contain anything relevant to this check.
1 · Delivery
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Does a non-rendering crawler receive the markup at all?
How this is measured
Checks for JSON-LD in the raw HTML without running JavaScript. Markup added only after client-side rendering will not appear here. Microdata and RDFa are noted but not audited. Playbook section · How to fix it
2 · Validity
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Does every block contain valid JSON and use a schema.org context?
How this is measured
Checks the JSON syntax and @context declaration of each block. Invalid blocks are quoted so you can find and fix them. Use Schema Markup Validator for full vocabulary conformance. Playbook section · How to fix it
3 · Integrity
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Does the entity graph connect consistently?
How this is measured
Checks whether @id values are unique, references resolve within the page, entities are defined more than once, and an Organization or Person node provides a stable identity. Playbook section · How to fix it
4 · Truth
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Do the page and the outside world agree with what the markup asserts?
How this is measured
Compares the marked-up headline with the visible title, checks author visibility and date consistency, and tests up to 10 sameAs and logo URLs. A responding URL does not prove that it identifies the right entity, so a manual review is still required. Playbook section · How to fix it
Manual content review
Human judgment
Is every fact in the markup also visible on the page, including prices, ratings, addresses, and descriptions?
This step requires human judgment. Compare the markup with the rendered page and confirm that every statement is visible and accurate. If a block cannot be kept consistent with the page, update or remove the markup. Playbook section
Why there is no overall score
A single score can hide very different problems and does not tell you what to fix. Following the schema audit playbook, this checker reports each finding separately instead. The citability checker uses the same evidence-first approach.
Each verdict includes something you can verify on the page, such as a conflicting @id, an unavailable sameAs URL, or a date set in the future.
How the check works
Fetch the raw HTML without running JavaScript and collect every JSON-LD script block.
Parse each block and check its @context declaration. If a block is invalid, show the relevant source text.
Inspect the entity graph for conflicting @id values, unresolved references, duplicate definitions, and missing Organization or Person nodes.
Compare machine-checkable statements with the page, including the headline, author, and dates. Test up to 10 sameAs and logo URLs for availability.
Report a separate result for each stage and include evidence for every warning or issue.
What this check can and cannot judge
This is a single-page check. An @id defined on another page may appear unresolved here. Use the schema audit playbook when you need to inspect connections across the whole site.
This tool checks JSON syntax, @context, graph consistency, and a limited set of page comparisons. Use Schema Markup Validator for vocabulary conformance and Rich Results Test for Google feature eligibility.
URL probes check availability, not identity. A responding sameAs URL may still point to a parent brand or another entity with the same name. Targets that block the probe are marked for manual verification; only a clear 404 or 410 is treated as unavailable.
Clean structured data does not guarantee more AI citations. Its practical value is accurate, consistent entity information. The supporting evidence is summarized in the playbook’s first section.
A page without structured data is not automatically a failure. If you decide to add it, Schema Implementation explains how to publish and verify it.
Frequently asked questions
Why doesn’t this tool give a 0–100 schema score?
A single score can hide whether the problem is delivery, invalid JSON, a conflicting identity, or a mismatch with the page. Separate findings are more useful because each one shows what happened and what to review.
The Schema Markup Validator says my page is fine. Why does this tool still find problems?
Schema Markup Validator focuses on vocabulary conformance. This checker also looks for delivery problems, conflicting @id definitions, unresolved references, page-to-markup mismatches, and unavailable identity URLs. The tools answer different questions and are best used together.
My markup shows up in devtools, but this tool says there is none. Which is right?
Developer tools often show the rendered DOM after JavaScript has run, while this checker reads the raw response body. If the markup appears only after rendering, both results can be correct. Publish the JSON-LD in the server response if non-rendering crawlers need to receive it.
Is broken JSON-LD harmless, since parsers just ignore it?
Structured-data parsers ignore invalid JSON-LD, but some systems may still process the script content as page text. Fix or remove invalid blocks, especially when they contain statements that conflict with the visible page.
Should I remove my FAQPage or HowTo markup now that Google dropped rich results for them?
Not solely because the rich result was discontinued. Accurate FAQPage or HowTo markup can still be valid Schema.org. Keep it if it remains correct and useful to maintain; update or remove it if it is outdated or conflicts with the page.
If I fix everything this tool finds, will AI engines cite me more?
There is no reliable evidence that clean JSON-LD alone increases AI citations. Treat structured data as a way to publish accurate, consistent entity information, not as a ranking or citation guarantee.