Build and debug
JSON Validator
Use this JSON Validator to validate JSON with syntax, structure, and validation checks. Add JSON Schema when you have it, or leave the schema blank for quick syntax review.
Developer ToolsPublished Mar 12, 2026Last reviewed Mar 12, 2026
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How to use JSON Validator
- 1
Paste the data JSON first
Start with the payload you actually need to verify. If the JSON itself is malformed, the tool can tell you that before schema logic gets in the way.
- 2
Add a schema only when your workflow has one
Leave the schema field blank for syntax-only checks, or paste a JSON Schema document when you want contract validation on top of plain parsing.
- 3
Review whether the issue is in the data or the schema
Use the result panel to separate parser failures, schema failures, and data-validation failures so you know what actually needs to be fixed next.
Workflow
Use JSON Validator when you need a valid or invalid answer first
JSON Validator is useful when the first question is not readability but correctness. Paste the payload, run a syntax check, and decide whether the JSON is valid before you send it to another system or teammate. If a schema already exists, add it and move from basic parsing into contract validation without switching tools.
That makes the workflow practical for webhook debugging, QA handoff, or automation setup. You can validate JSON quickly even when the schema is still being drafted, then layer in stricter checks when the contract is ready.
How it works
Syntax checks and schema checks stay separate on purpose
The tool runs a clear sequence: parse the data JSON, parse the schema if one exists, then validate the parsed data against the parsed schema. That order matters because it tells you whether the broken piece is the payload itself or the contract you are trying to enforce.
Remote $ref fetches, custom keywords, and plugin-driven schema extensions are intentionally outside the current scope. The result is a validator with predictable behavior instead of a page that quietly depends on hidden network access or project-specific extensions.
Limits
Current limits favor deterministic validation over broad compatibility
This version supports internal references and standard JSON Schema flow, but it stops short of becoming a full schema platform. Unknown keywords are surfaced instead of ignored, remote references are rejected, and large or deeply nested inputs stop before they make the page unusable.
Those limits are deliberate. They keep the browser-based validator dependable for everyday checks, but they also make it clear when a heavier local toolchain or application-level validation setup is the better fit.
Compare tools
When to use JSON Validator instead of JSON Formatter or JSON Diff
Use JSON Formatter when the payload already looks valid and you mainly want readable indentation. Use JSON Validator when you need a real valid or invalid answer, schema support, or a clean explanation of whether the data or the schema is wrong.
Use JSON Diff instead when both inputs are valid and the real question is what changed between left and right. In other words, use JSON Validator when correctness is the decision point, and use the sibling tools when readability or comparison is the real job.
Example scenarios
Order payload
Frequently asked questions
What happens if the schema field is blank?
Whitespace-only schema input skips schema parsing and schema validation. The tool then runs a syntax-only validation pass on the data JSON so you can still validate JSON before the schema exists or before a teammate sends it over.
Are remote $ref values supported?
No. JSON Validator supports internal references only, so remote `$ref` values are rejected before validation starts. That keeps the check deterministic, browser-friendly, and free from hidden network fetches.
Does format invalidate data in v1?
No. In this version, `format` behaves like an annotation rather than a hard validation rule, so it does not invalidate the data by itself. That keeps the current rule set simpler and more predictable.
How are unknown schema keywords handled?
Unknown or custom keywords are surfaced as schema problems instead of being accepted silently. That makes the result stricter, but also easier to trust during debugging and contract review.
How are duplicate keys handled?
Both the data editor and the schema editor follow `JSON.parse` semantics, so duplicate object keys keep the last parsed value before validation begins. If duplicates matter in your workflow, you should fix them before relying on the result.