JSON Schema compatibility topic

JSON Schema enum and type compatibility debugging tools

A workflow for enum mismatches, number/string drift, boolean stringification, array-shape changes, and API field compatibility checks.

Direct answer

When an API release introduces enum mismatches, number values start arriving as strings, booleans are stringified, or array item shapes change, validate with JSON Schema first, then inspect real paths with key-path extraction, JSON Pointer, JSONPath, and Deep Diff.

Long-tail searches covered
JSON Schema enum errorJSON Schema type mismatchJSON number string driftJSON boolean stringAPI field type changeJSON Schema compatibilityenum mismatchAPI contract validation

Common lookup scenarios

A status field changes from draft/published to processing and breaks enum validation

orderId, total, or paid starts arriving as strings

Array item structures change after an API release

Review number, integer, and boolean drift between backend and frontend contracts

Check schema compatibility before release sign-off

Recommended workflow

  1. Format the JSON and confirm it parses
  2. Use Schema validation to find enum, type, and array-path failures
  3. Use key paths and Pointer to verify the real field location
  4. Use JSONPath to inspect arrays and nesting
  5. Use Deep Diff on v1/v2 payloads before updating the schema

Related tool entries

A workflow for enum mismatches, number/string drift, boolean stringification, array-shape changes, and API field compatibility checks.

FAQ

When an API release introduces enum mismatches, number values start arriving as strings, booleans are stringified, or array item shapes change, validate with JSON Schema first, then inspect real paths with key-path extraction, JSON Pointer, JSONPath, and Deep Diff.

Does an enum mismatch always mean the backend is wrong?

No. The schema may be outdated, the field may have moved, or the business rule may have changed. Confirm the real payload and contract first.

Why is number or boolean stringification risky?

It can break sorting, calculations, UI logic, database mapping, and downstream schema checks. Type drift is often subtle but release-breaking.

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