JSON Schema Validator

Validate JSON data against a JSON Schema with detailed error reporting.

JSON Data

JSON Schema

Introduction

JSON Schema Validator checks whether a JSON document conforms to a schema you control. Paste your data on one side, your schema on the other, hit Validate, and the tool reports exactly which properties match, which are missing, and which have the wrong type.

JSON Schema is the standard contract format for REST APIs, configuration files, and event payloads. Validating against a schema before deploy lets you catch breaking changes — a renamed field, a tightened enum, a now-required property — before they reach production consumers. The tool covers the core Draft-07 keywords: type, required, properties, items, enum, minimum, maximum, minLength, maxLength, and pattern.

Validation runs client-side. Your data and schema never leave the tab, which matters when either contains production records, credentials, or proprietary contracts.

How to Use

Paste your JSON data into the left editor.
Paste the JSON Schema into the right editor.
Click Validate — errors are listed with the failing property path and reason.
Edit either pane and re-validate to iterate on contract changes.
Copy the cleaned-up schema back into your repository when you're done.

Examples

Example 1: User object — passes validation

Input

// Data
{
  "id": 42,
  "email": "ada@example.com",
  "age": 36
}

// Schema
{
  "type": "object",
  "required": ["id", "email"],
  "properties": {
    "id":    { "type": "integer" },
    "email": { "type": "string",
               "pattern": "^.+@.+$" },
    "age":   { "type": "integer",
               "minimum": 0 }
  }
}

Output

Valid — 0 errors.

All required properties are present.
All type constraints satisfied.
Pattern "^.+@.+$" matches "ada@example.com".

Example 2: Nested array with an item-level constraint

Input

// Data
{
  "tags": ["beta", "", "launch"]
}

// Schema
{
  "type": "object",
  "properties": {
    "tags": {
      "type": "array",
      "items": {
        "type": "string",
        "minLength": 1
      }
    }
  }
}

Output

Invalid — 1 error:

  /tags/1
    minLength: expected string with length >= 1,
    got "" (length 0)

Example 3: Missing required field

Input

// Data
{
  "title": "Launch brief"
}

// Schema
{
  "type": "object",
  "required": ["title", "author"],
  "properties": {
    "title":  { "type": "string" },
    "author": { "type": "string" }
  }
}

Output

Invalid — 1 error:

  /
    required: missing property "author"
    (required fields: title, author)

JSON specification reference

Quick reference from RFC 8259. The converter enforces these rules on input; anything outside them is rejected or normalized.

Element	Meaning	Example
Object	Unordered set of key/value pairs	{"a": 1}
Array	Ordered list of values	[1, 2, "x"]
String	Unicode, double-quoted only	"hello"
Number	IEEE 754 double, no NaN / Infinity	3.14
Literal	true / false / null only	null

Common invalid forms

{'a': 1}  // single quotes not allowed
{a: 1}    // unquoted keys
{"a": 1,} // trailing comma
NaN       // not permitted by RFC 8259

Key Features

Draft-07 keyword coverage: all of the core validation keywords most contracts rely on, including enum, pattern, and numeric bounds.
Recursive validation: nested objects and arrays are walked to any depth, with errors reported at the exact JSON path that failed.
Detailed error messages: each failure names the keyword, the expected value, and the actual value so you can fix it without re-reading the spec.
Side-by-side editors: data and schema sit next to each other, so editing one while watching the other is frictionless.
Parse-error detection: if either pane contains malformed JSON, the tool surfaces the syntax error before attempting validation.
Client-side only: no payload is uploaded; sensitive production data stays in your tab.

Frequently Asked Questions

What's the difference between required and type?

required says the property must exist on the object. type says a value, if present, must match a JSON type (string, number, boolean, object, array, null). Combine them to demand that a field is present and correctly typed.

Which draft is supported?

Draft-07 core keywords. Keywords like $ref, allOf, anyOf, oneOf, and if/then/else from the later drafts are not executed.

Does the validator follow $ref references?

Not in this build. Inline the referenced schema into a single document before pasting it in, or use a bundler to pre-resolve the references.

What does an error path look like?

Errors are reported as JSON Pointer paths: / for the root, /users/2/email for the email field of the third user. That makes it easy to locate the offending value in a large document.

Will invalid JSON in either pane crash the validator?

No. A parse error in the data or schema is shown in place of validation results, with the line and column of the syntax failure so you can fix it quickly.

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JSON Schema Validation: Protecting Your API with Data Contracts11 min read

JSON Schema Validator

Validate JSON data against a JSON Schema with detailed error reporting.

JSON Data

JSON Schema

Introduction

Validation runs client-side. Your data and schema never leave the tab, which matters when either contains production records, credentials, or proprietary contracts.

How to Use

Paste your JSON data into the left editor.
Paste the JSON Schema into the right editor.
Click Validate — errors are listed with the failing property path and reason.
Edit either pane and re-validate to iterate on contract changes.
Copy the cleaned-up schema back into your repository when you're done.

Examples

Example 1: User object — passes validation

Input

// Data
{
  "id": 42,
  "email": "ada@example.com",
  "age": 36
}

// Schema
{
  "type": "object",
  "required": ["id", "email"],
  "properties": {
    "id":    { "type": "integer" },
    "email": { "type": "string",
               "pattern": "^.+@.+$" },
    "age":   { "type": "integer",
               "minimum": 0 }
  }
}

Output

Valid — 0 errors.

All required properties are present.
All type constraints satisfied.
Pattern "^.+@.+$" matches "ada@example.com".

Example 2: Nested array with an item-level constraint

Input

// Data
{
  "tags": ["beta", "", "launch"]
}

// Schema
{
  "type": "object",
  "properties": {
    "tags": {
      "type": "array",
      "items": {
        "type": "string",
        "minLength": 1
      }
    }
  }
}

Output

Invalid — 1 error:

  /tags/1
    minLength: expected string with length >= 1,
    got "" (length 0)

Example 3: Missing required field

Input

// Data
{
  "title": "Launch brief"
}

// Schema
{
  "type": "object",
  "required": ["title", "author"],
  "properties": {
    "title":  { "type": "string" },
    "author": { "type": "string" }
  }
}

Output

Invalid — 1 error:

  /
    required: missing property "author"
    (required fields: title, author)

JSON specification reference

Quick reference from RFC 8259. The converter enforces these rules on input; anything outside them is rejected or normalized.

Element	Meaning	Example
Object	Unordered set of key/value pairs	{"a": 1}
Array	Ordered list of values	[1, 2, "x"]
String	Unicode, double-quoted only	"hello"
Number	IEEE 754 double, no NaN / Infinity	3.14
Literal	true / false / null only	null

Common invalid forms

{'a': 1}  // single quotes not allowed
{a: 1}    // unquoted keys
{"a": 1,} // trailing comma
NaN       // not permitted by RFC 8259

Key Features

Draft-07 keyword coverage: all of the core validation keywords most contracts rely on, including enum, pattern, and numeric bounds.
Recursive validation: nested objects and arrays are walked to any depth, with errors reported at the exact JSON path that failed.
Detailed error messages: each failure names the keyword, the expected value, and the actual value so you can fix it without re-reading the spec.
Side-by-side editors: data and schema sit next to each other, so editing one while watching the other is frictionless.
Parse-error detection: if either pane contains malformed JSON, the tool surfaces the syntax error before attempting validation.
Client-side only: no payload is uploaded; sensitive production data stays in your tab.

Frequently Asked Questions

What's the difference between required and type?

Which draft is supported?

Draft-07 core keywords. Keywords like $ref, allOf, anyOf, oneOf, and if/then/else from the later drafts are not executed.

Does the validator follow $ref references?

Not in this build. Inline the referenced schema into a single document before pasting it in, or use a bundler to pre-resolve the references.

What does an error path look like?

Errors are reported as JSON Pointer paths: / for the root, /users/2/email for the email field of the third user. That makes it easy to locate the offending value in a large document.

Will invalid JSON in either pane crash the validator?

No. A parse error in the data or schema is shown in place of validation results, with the line and column of the syntax failure so you can fix it quickly.