JSON Best Practices Checker

The JSON Best Practices Checker reviews a JSON payload for maintainability risks that validation alone never catches. A payload can be syntactically valid and semantically correct while still being difficult to maintain: keys that mix camelCase and snake_case, objects nested six levels deep when two would suffice, arrays that mix types, or top-level structures with a hundred fields that should be grouped. The checker flags these patterns so you can address them before they become entrenched technical debt.

1. Paste your JSON payload into the input panel.
2. The checker runs a set of heuristics covering naming conventions, nesting depth, structural consistency, and array type uniformity.
3. Review each flagged item: every finding includes what was detected and why it matters.
4. Prioritize fixes by severity — deep nesting and mixed naming conventions compound across a codebase, while single oversized objects are easier to isolate.
5. Apply corrections in your source schema or generation code, then paste the updated payload to re-check.

• Mixed naming conventions (userId alongside user_id in the same object) that cause consumers to handle two different patterns
• Nesting deeper than necessary, which makes paths verbose and refactoring expensive when requirements change
• Arrays that contain both objects and primitives, creating branching logic in every consumer
• Oversized flat objects with no grouping, where a field like shippingStreet, shippingCity, and shippingZip should live inside an address sub-object
• Boolean fields named as questions (is_active, has_permission) mixed with noun-style fields in the same schema
• null used as a stand-in for missing arrays or objects rather than an empty collection

The following payload contains several common maintainability issues in one document:

{
  "userId": 882,
  "user_name": "carlos",
  "Email": "[email protected]",
  "active": true,
  "address_street": "12 Maple Ave",
  "address_city": "Toronto",
  "address_zip": "M5V 2T6",
  "orders": [
    { "id": "O-001", "total": 120.00 },
    "pending-order-placeholder"
  ],
  "metadata": {
    "source": { "channel": { "detail": { "code": "REF-7" } } }
  }
}

The checker would flag: three different key naming styles (userId, user_name, Email), flat address fields that should be grouped, a mixed-type array in orders, and four levels of nesting in metadata for a single value.

• API design review. Before publishing a new endpoint, run the checker on a representative response to catch patterns that will frustrate consumers and be expensive to change later.
• Platform governance. Your team is standardizing payload shapes across multiple services. Use the checker to audit existing endpoints and measure how far they diverge from the agreed conventions.
• Schema review before schema authoring. Before writing a formal JSON Schema, run a best practices check to identify structural problems that the schema would otherwise enshrine.
• Onboarding audits. You are integrating a third-party API and want a quick read on how maintainable its payload structure is before committing to deep coupling with it.

• JSON Validator — validate syntax first; the best practices checker assumes the input is already valid JSON
• JSON Structure Analyzer — get objective depth and key-count metrics to supplement the qualitative findings from the checker
• Common JSON Mistakes — reference for the specific errors and patterns the checker is designed to catch
• JSON Schema Basics — formalize the conventions you want to enforce after identifying problems with the checker