$ Validate JSON against a schema
Paste a JSON Schema and a JSON document to validate. Get path-level error messages instantly.
Schema & Document
Paste your JSON Schema and the JSON document to validate.
Validation result
The document is valid against the schema.
All constraints in the schema are satisfied. The document is valid.
Why this tool exists
Vultio JSON Schema Validator helps you answer a more useful question than “is this JSON valid?”: does this JSON actually satisfy the contract your system expects? That distinction matters in APIs, config files, event payloads, migrations, and any workflow where structure and constraints are part of correctness.
A JSON document can parse perfectly and still be wrong because a field is missing, an enum value drifted, an array is empty when it should not be, or an unexpected property slipped in during a backend change. Schema validation catches those contract-level failures before they move deeper into your stack.
This tool is especially useful during integration work because it shows errors at the exact path that failed. That makes it easier to debug payloads collaboratively instead of just saying “the request body is invalid” with no actionable detail.
In practice, schema validation becomes a bridge between teams. It gives frontend, backend, QA, and data engineers a shared contract they can discuss using exact fields and constraints instead of vague assumptions about what a payload “should look like.”
Common use cases
Example input / output
Required field missing
Type and value constraint failure
Unexpected field blocked by schema
Common errors
cause:The schema panel contains a syntax error such as a trailing comma, missing quote, or malformed nesting before validation even begins.
fix:Format the schema with the JSON Formatter, repair the JSON syntax, then validate again.
cause:The schema explicitly sets additionalProperties: false, but the document includes a field that is not declared in properties.
fix:Either add the field to the schema intentionally or remove it from the payload if it should not be there.
cause:Many schema errors come from subtle issues such as strings instead of numbers, arrays with zero items, enum mismatches, or nested required properties that are missing deeper in the document.
fix:Read the full failing path and inspect the exact field type and constraint there instead of only looking at the top-level shape.
cause:Your production stack may rely on a different JSON Schema draft, external references, OpenAPI wrappers, or custom keywords that are outside this focused validator workflow.
fix:Use this tool for fast contract debugging, then confirm draft-specific or platform-specific behavior in the exact validator or CI environment used by your application.
How developers use it in practice
When an API contract is still moving, validate sample responses early. It is much cheaper to catch a wrong field type in the payload than to debug downstream rendering or runtime parsing failures later.
Path-level errors like $.user.roles[0] tell you exactly where the contract broke. That makes the tool useful not only for validation but also for communicating bugs clearly to backend or data engineers.
The strongest API docs include both the schema and a real sample document. Use the validator to keep those examples honest instead of letting them drift away from the contract.
When a large payload is failing in multiple places, isolate the subtree around the first reported path. Fixing one concrete mismatch often reveals whether the rest of the issues are copies of the same contract mistake.
When not to use this tool
Limits and implementation notes
This validator focuses on a practical subset centered on draft-07-style keywords. Advanced references and every draft-specific feature are not the goal here.
The tool validates the schema and document you paste. It does not resolve a full OpenAPI document, remote refs, or environment-specific API metadata.
First the schema and document must parse as JSON, then the contract rules are applied. A valid parse does not imply a valid schema match.
Passing validation does not guarantee that the schema itself is maintainable or expressive enough. Teams should still review naming, reuse, optionality, and versioning strategy for long-lived contracts.
Related guides
Standards & references
Related tools
Frequently asked questions
What is JSON Schema validation?
JSON Schema is a vocabulary for describing the structure of JSON data. A validator checks whether a JSON document conforms to a schema, reporting exactly which fields fail and why.
Which JSON Schema draft is supported?
The validator supports the core keywords from JSON Schema draft-07: type, properties, required, additionalProperties, items, minLength, maxLength, minimum, maximum, pattern, enum, const, allOf, anyOf, oneOf, and not.
What does a validation error message look like?
Each error includes the JSON path to the failing value (e.g. $.user.age) and a human-readable message describing the constraint that was violated.
Can I validate arrays and nested objects?
Yes. The validator recurses through all nested objects and arrays, reporting errors at the exact path where each violation occurs.
Is my JSON sent to a server?
No. Validation runs entirely in your browser. Neither the schema nor the JSON document is uploaded or transmitted anywhere.