JSON Schema Validator in your browser, no signup

JSON on its own carries no rules. A field can be a string in one record and a number in the next, a required value can simply be absent, and nothing complains until something downstream breaks in a confusing way. JSON Schema adds those rules: this field must be a string, this one is required, this number must be positive, this array needs at least one item. Validating against it moves failures to the moment the data arrives rather than three systems later. The keywords doing most of the work are few - type, required, properties, and the constraints like minimum, maxLength and pattern. The one that surprises people is additionalProperties: by default a schema permits fields it never mentioned, so a payload with a misspelled key validates happily while the correctly spelled field is missing. Setting it to false is what turns a typo into an error. Validation runs in your browser.

You should not have to open an IDE to format a snippet from Slack, tidy a JSON blob, or check a hash. Paste it here, copy the result, move on.

JSON Schema Validator is a good fit when validating an API request or response against its contract.

In plain English

JSON Schema Validator is built around a few practical wins, not a long feature list:

• Catches malformed data at the boundary rather than deep inside your application.
• Reports the path to each failure, so debugging is immediate.
• Runs in your browser - API payloads containing real data are never transmitted.
• Lets you develop a schema iteratively against real examples.
• No account and no size limit.

How to run it

1. Paste your schema. The rules the data must satisfy - types, required fields and constraints.
2. Paste the JSON data. A real payload rather than an idealised one. Edge cases are where schemas earn their keep.
3. Read the validation result. Failures are reported with the path to the offending field, so you know exactly where to look.
4. Test the failing cases too. A schema that accepts everything is not validating anything. Confirm bad data is actually rejected.

Real situations

• Validating an API request or response against its contract.
• Checking a configuration file before deployment.
• Testing a schema you are writing against real sample data.
• Debugging why a payload is being rejected by a service.
• Documenting the expected shape of data for other developers.

Small habits that help

• Set additionalProperties to false when you want typos caught. By default a schema silently allows fields it never declared.
• Test with invalid data as well as valid. A schema that passes everything gives false confidence.
• Use "required" explicitly - listing a field under properties does not make it mandatory, which is a very common misunderstanding.
• Note that type: "number" accepts decimals; use "integer" when you mean whole numbers only.
• If the JSON itself will not parse, fix that first with the JSON Formatter - a syntax error is not a schema failure.

Skip these

• Assuming a field listed in properties is required. It is not - required is a separate array.
• Leaving additionalProperties at its default, so a misspelled key passes validation while the real field is missing.
• Using "number" where "integer" was meant, letting 3.7 through as a quantity.
• Only testing data you expect to pass, so the schema is never proven to reject anything.
• Writing a schema so strict it breaks on every legitimate future addition to the payload.

Does anything leave your device?

JSON Schema Validator runs in your browser. The file or text you paste stays on your device. There is no account, and nothing is stored on a ToolBox server for this job.

Related tools worth opening next

If this is one step in a longer job, these usually come after it:

• JSON Schema Generator - Generate a JSON Schema from sample JSON data
• JSON Formatter - Format and validate JSON data
• JSON Compare - Compare two JSON documents by structure, ignoring key order and formatting

FAQ

What JSON Schema draft/version does this support?

It follows standard JSON Schema conventions covering the most commonly used validation keywords (types, required fields, patterns, ranges) - check specific advanced/newer draft features against your schema if you rely on less common keywords.

What happens if my JSON data fails validation?

The tool reports which parts of the data violate the schema - such as a missing required field, wrong data type, or a value outside an allowed range - so you can pinpoint and fix the issue.

Do I need to write the schema myself?

For this tool, yes. If you have sample data but no schema, the JSON Schema Generator produces one from it, which you can then tighten by hand.

Why does my schema accept a field that should not be there?

Because additionalProperties defaults to true, so any field the schema does not mention is allowed. Set it to false and unexpected keys - including misspelled ones - become validation errors.

Why is a missing field not reported as an error?

Listing a field under properties describes it but does not make it mandatory. Fields are only required when named in the separate "required" array - this catches almost everyone at least once.

Is my data uploaded anywhere?

No. Validation runs in your browser, which matters because the payloads people validate are usually real API traffic containing customer data.

Open the JSON Schema Validator when you are ready. It is free, and you do not need an account.