JSON Schema Validator - QuickToolFlow

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Test JSON paths against JSON data. Query nested objects, arrays, indexes, and wildcard matches.

Example

Validate an API user object

The validator reports whether required fields exist and whether nested values match the expected type and constraints.

Input


                        {
  "id": 42,
  "email": "ada@example.com",
  "roles": ["admin"]
}

Output


                        {
  "type": "object",
  "required": ["id", "email"],
  "properties": {
    "id": { "type": "integer" },
    "email": { "type": "string", "pattern": "^[^@]+@[^@]+\\.[^@]+$" },
    "roles": { "type": "array", "items": { "type": "string" } }
  }
}

Detect a string where a number is expected

The JSON syntax is valid, but schema validation can still flag type drift that would break calculations or database imports.

Input


                        {
  "sku": "plan-pro",
  "price": "29.00"
}

Output


                        {
  "type": "object",
  "required": ["sku", "price"],
  "properties": {
    "sku": { "type": "string" },
    "price": { "type": "number" }
  }
}

Limit status values with enum

Enum checks are useful when API clients should only accept a controlled set of states.

Input


                        {
  "id": "order_123",
  "status": "processing"
}

Output


                        {
  "type": "object",
  "properties": {
    "status": { "type": "string", "enum": ["draft", "paid", "shipped", "cancelled"] }
  }
}

Practical Notes

This quick validator focuses on common JSON Schema keywords. Use a full schema library in production test suites when you need complete draft compatibility.
Validate small representative samples first. Large payloads are easier to debug after you reduce them to the failing branch.
Use JSON Formatter before schema validation when pasted data may contain syntax errors.
Pattern rules are interpreted as JavaScript regular expressions, so escape backslashes carefully in JSON strings.
Use required for fields that must exist, then add minLength, minimum, or enum rules when values also need constraints.
When a schema feels noisy, start with only the fields your application truly depends on and expand from there.

How to Use

1. Paste your JSON data into the JSON input panel.
2. Paste or write a JSON Schema in the schema panel.
3. Click Validate to check the data against the schema rules.
4. Review each path-level error and adjust either the data or schema.
5. Copy the validation report if you need to share the result.

Features

Validate JSON against common schema keywords
Supports type, required, properties, items, enum, const, and ranges
Shows readable error paths for nested objects and arrays
Includes a sample payload and schema for quick testing
Runs locally in your browser without uploading data
Copy a plain-text validation report for debugging or review
Useful for quick API contract checks before writing automated tests
Helps separate syntax errors from data-shape errors

Use Cases

Checking API response shapes before adding frontend handling
Reviewing fixture data for tests and documentation
Validating config-like JSON before committing changes
Debugging required fields, nested properties, arrays, and enums
Confirming webhook payloads contain the fields your integration expects
Reviewing sample API documentation before sharing it with consumers

Frequently Asked Questions

What does this JSON Schema Validator check?

It checks common JSON Schema constraints such as type, required, properties, items, enum, const, minimum, maximum, minLength, maxLength, minItems, maxItems, pattern, and additionalProperties.

Is this a complete JSON Schema draft implementation?

No. It is designed for fast browser checks of common schema rules. For advanced keywords such as oneOf, anyOf, allOf, refs, conditionals, and custom formats, use a dedicated JSON Schema library in your build or test workflow.

Does my JSON data leave the browser?

No. Validation runs with JavaScript in your browser, so the pasted JSON and schema are not uploaded to a server.

Should I format JSON before validating it?

Yes. Formatting first makes syntax errors, missing commas, and nesting problems easier to spot before schema-level validation begins.

What is the difference between required and non-empty?

The required keyword means a property must exist. It does not always mean the value is useful. Add rules such as minLength, minimum, minItems, or enum when empty or out-of-range values should fail.

Can schema validation replace API tests?

No. Schema validation is a strong boundary check, but API tests should still cover behavior, authorization, error states, pagination, and business rules.