What is Schema Markup Validator?
A Schema Markup Validator checks structured data for machine-readable problems before you publish or troubleshoot a page. On this site, the validator focuses on JSON-LD because it is widely used and easier to inspect safely than trying to infer every possible microdata or RDFa relationship from arbitrary HTML. It checks JSON syntax, looks for linked-data fields such as `@context` and `@type`, and exposes the parsed structure so you can review what the markup actually says.
Structured data is easy to break with one missing comma, an incorrectly nested object or a field copied from an unrelated example. A page can render perfectly for users while its JSON-LD silently fails to parse. Validation catches those structural problems early, but it should not be confused with search-engine rich-result eligibility, which has additional product-specific requirements.
How to use the Schema Markup Validator
- 1Copy the JSON-LD object from your page source or implementation code.
- 2Paste the JSON-LD into the validator without the surrounding `<script>` tag if possible.
- 3Run validation and resolve JSON syntax errors first.
- 4Review detected `@context` and `@type` values to make sure they describe the visible page honestly.
- 5After structural validation, use the relevant search-engine testing tool if your goal is a specific rich result.
Understanding the results
- Valid JSON means the text is syntactically parseable; it does not mean every Schema.org property is semantically correct.
- A missing `@context` warning indicates the object may not clearly declare the vocabulary it uses.
- A detected `@type` tells you which entity the object claims to represent.
- Nested objects should mirror real relationships on the page rather than exist only because a sample template included them.
Common problems
- Trailing commas copied from JavaScript objects into strict JSON.
- Smart quotes pasted from a rich-text editor.
- Using a schema type that does not match the page's main entity.
- Adding ratings, reviews, prices or authors that are not visible or real.
- Publishing duplicate JSON-LD blocks from both a plugin and custom code.
How to fix them
- Convert JavaScript-style objects into strict JSON before embedding them.
- Remove unsupported or fictional properties instead of filling them with placeholder values.
- Keep one authoritative source of structured data for each entity where possible.
- Validate after deployment because templates, escaping and minification can change the final output.
Schema.org structured data best practices
- Describe real entities and visible facts.
- Prefer the most specific appropriate Schema.org type without forcing an unrelated subtype.
- Use absolute URLs for important identifiers and page references.
- Treat structured data as a representation of the page, not a separate SEO story.
Practical example
What this tool cannot tell you
This validator checks syntax and basic linked-data structure. It does not guarantee that Google, Bing or another platform will use the markup, and it does not replace product-specific rich result documentation.
Frequently asked questions
Is valid schema guaranteed to produce rich results?+
No. Valid syntax is only one requirement. Search engines apply feature-specific policies and decide whether to show enhanced results.
Does the validator support microdata?+
This implementation focuses on pasted JSON-LD. Use a browser or search-engine testing tool when you need to inspect microdata rendered in HTML.
What is `@context`?+
It identifies the vocabulary used by the JSON-LD, commonly `https://schema.org`.
Can one page have several schema types?+
Yes, when the page genuinely contains multiple related entities. They should be connected logically rather than dumped into unrelated blocks.
Should schema include hidden information?+
Structured data should accurately represent page content and real facts, not hidden promotional claims created only for crawlers.
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