JSONLint

Paste your schema on the left and data on the right to validate:

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What is JSON Schema?

JSON Schema is a declarative language for defining the structure of JSON data. Think of it as TypeScript types, but for JSON—you define what properties exist, their types, and any constraints. Then you can validate any JSON document against that schema.

When to Use Schema Validation

  • API request validation — Reject malformed requests before they hit your business logic
  • Configuration files — Catch typos in config before deployment
  • Form data — Validate user input on both client and server
  • Data pipelines — Ensure incoming data matches expected format
  • API documentation — Schemas serve as living documentation

Quick Reference

Basic Types

{ "type": "string" }
{ "type": "number" }
{ "type": "integer" }
{ "type": "boolean" }
{ "type": "null" }
{ "type": "array" }
{ "type": "object" }

String Constraints

{
  "type": "string",
  "minLength": 1,
  "maxLength": 100,
  "pattern": "^[a-z]+$",
  "format": "email"  // or: uri, date-time, uuid
}

Number Constraints

{
  "type": "number",
  "minimum": 0,
  "maximum": 100,
  "exclusiveMinimum": 0,
  "multipleOf": 0.01
}

Object with Required Properties

{
  "type": "object",
  "properties": {
    "id": { "type": "integer" },
    "name": { "type": "string" },
    "email": { "type": "string", "format": "email" }
  },
  "required": ["id", "name"],
  "additionalProperties": false
}

Array Validation

{
  "type": "array",
  "items": { "type": "string" },
  "minItems": 1,
  "maxItems": 10,
  "uniqueItems": true
}

Complete Example

Here's a schema for a user profile API response:

{
  "$schema": "http://json-schema.org/draft-07/schema#",
  "type": "object",
  "properties": {
    "id": { 
      "type": "integer",
      "minimum": 1
    },
    "username": { 
      "type": "string",
      "minLength": 3,
      "maxLength": 20,
      "pattern": "^[a-zA-Z0-9_]+$"
    },
    "email": { 
      "type": "string", 
      "format": "email" 
    },
    "role": { 
      "type": "string",
      "enum": ["admin", "user", "guest"]
    },
    "profile": {
      "type": "object",
      "properties": {
        "bio": { "type": "string", "maxLength": 500 },
        "avatar": { "type": "string", "format": "uri" }
      }
    },
    "createdAt": { 
      "type": "string", 
      "format": "date-time" 
    }
  },
  "required": ["id", "username", "email", "role"],
  "additionalProperties": false
}

Understanding Validation Errors

When validation fails, you'll see errors like:

  • must have required property 'name' — A required field is missing
  • must be string — Wrong type (e.g., number instead of string)
  • must match format "email" — String doesn't match the format
  • must NOT have additional properties — Unknown field whenadditionalProperties: false
  • must be >= 0 — Number violates minimum constraint

Pro Tips

  • 💡 Start strict — Use "additionalProperties": false to catch typos in property names. You can always loosen later.
  • 💡 Use enums for known values — Instead of just string, use "enum": ["active", "inactive"] when you know the valid values.
  • 💡 Add descriptions — Include "description" fields for documentation that travels with your schema.
  • 💡 Test edge cases — Validate with empty objects, null values, and boundary numbers to ensure your schema handles them correctly.

Supported Draft Version

This validator uses Ajv and supports JSON Schema draft-07 by default. Most draft-04 and draft-06 schemas will also work.

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