JSON Validator

Validate, format, and fix JSON data with helpful error messages and suggestions.

When to Use This Skill

Use this skill when you need to:

• Validate JSON syntax and structure
• Format/prettify JSON data
• Fix common JSON errors
• Convert between JSON and other formats
• Analyze JSON structure

Validation

When validating JSON:

1. Check syntax: Identify syntax errors with line numbers
2. Provide context: Show the problematic section
3. Suggest fixes: Offer specific corrections
4. Explain issues: Describe what's wrong and why

Common JSON Errors to Check

• Missing or extra commas
• Unclosed brackets/braces
• Unquoted keys
• Trailing commas (invalid in strict JSON)
• Single quotes instead of double quotes
• Comments (not allowed in JSON)
• Undefined/NaN/Infinity values

Example Validation Output

❌ JSON Validation Failed

Line 5: Trailing comma after last object property
  "name": "example",
  "value": 123,  ← Remove this comma
}

✅ Suggested fix:
{
  "name": "example",
  "value": 123
}

Formatting

When formatting JSON:

1. Use 2-space indentation (standard)
2. Sort keys alphabetically (optional, ask user)
3. Remove unnecessary whitespace
4. Ensure consistent structure

Example

Input (minified):

{"name":"test","items":[1,2,3],"active":true}

Output (formatted):

{
  "name": "test",
  "items": [
    1,
    2,
    3
  ],
  "active": true
}

Fixing Common Issues

Trailing Commas

// ❌ Invalid
{
  "key": "value",
}

// ✅ Fixed
{
  "key": "value"
}

Single Quotes

// ❌ Invalid
{'key': 'value'}

// ✅ Fixed
{"key": "value"}

Unquoted Keys

// ❌ Invalid
{key: "value"}

// ✅ Fixed
{"key": "value"}

Comments

// ❌ Invalid
{
  // This is a comment
  "key": "value"
}

// ✅ Fixed
{
  "key": "value"
}

Conversion

When converting to/from JSON:

From JSON to other formats

• YAML: Preserve structure, use proper indentation
• TOML: Handle nested objects appropriately
• CSV: Flatten structure if needed, handle arrays
• XML: Choose appropriate tag names

To JSON from other formats

• Ensure proper escaping
• Validate the result
• Maintain data types (strings, numbers, booleans, null)

Analysis

When analyzing JSON structure:

1. Report schema:

   • Top-level type (object/array)
   • Key names and types
   • Nesting depth
   • Array sizes

2. Identify patterns:

   • Repeated structures
   • Optional fields
   • Data types used

3. Suggest improvements:

   • Inconsistent naming
   • Deep nesting issues
   • Large array optimization

Example Analysis

JSON Structure Analysis:

Type: Object
Keys: 3 (name, items, metadata)

Schema:
{
  "name": string,
  "items": array[3] of numbers,
  "metadata": {
    "created": string,
    "updated": string
  }
}

Depth: 2 levels
Total size: ~150 bytes

Best Practices

1. Always validate before formatting - Don't format invalid JSON
2. Show clear error messages - Include line numbers and context
3. Preserve data types - Don't convert numbers to strings unnecessarily
4. Handle edge cases - Empty objects, null values, Unicode characters
5. Ask before major changes - e.g., sorting keys, removing comments

Examples

Example 1: Validate and Fix

User request: "Validate this JSON and fix any errors"

Response:

Found 2 issues:

1. Line 3: Trailing comma after "name"
2. Line 5: Single quotes instead of double quotes

Here's the corrected JSON:
{
  "name": "example",
  "data": {
    "value": 42
  }
}

Example 2: Format

User request: "Format this JSON nicely"

Response:

{
  "users": [
    {
      "id": 1,
      "name": "Alice"
    },
    {
      "id": 2,
      "name": "Bob"
    }
  ],
  "total": 2
}

Example 3: Convert to YAML

User request: "Convert this JSON to YAML"

Response:

users:
  - id: 1
    name: Alice
  - id: 2
    name: Bob
total: 2