JSON schema validation
JSON Schema Validator
Validate JSON against the browser-safe JSON Schema subset used by DataDoctor and export a readable validation report.
Paste JSON data or load a valid sample.
Next workflow
Continue the preflight
After the tool runs
JSON Schema Validator review guide
Use the tool above first. The supporting notes below help you interpret the result, fix the right issues in the right order, and choose the next DataDoctor tool without pushing SEO content above the actual task.
Best input
checking whether JSON data matches a contract before it reaches an API, queue or import pipeline.
Output to keep
Keep the schema, sample data and validation report together so contract changes are traceable.
Next check
Refine required fields, enums and type rules, then validate a second sample before relying on the contract.
What it checks
JSON Schema Validator for real data work
JSON Schema Validator is for contract work: it checks whether the data shape matches the rules another system expects. Use it after the raw JSON or CSV parses cleanly.
- Required fields
- Field types
- Enums and constraints
- Readable schema errors
Fix these first
Common errors to review before downstream work
Most failures come from small file issues that become expensive only after an API call, import job or spreadsheet cleanup. Fix blocking errors first, then re-run the same tool before moving forward.
- Missing required properties
- Numbers sent as strings
- Unexpected enum values
- Nested objects with the wrong shape
Recommended workflow
Run the check in this order
When the report points to a path or row, fix the data when the source is wrong and fix the schema only when the contract was written too narrowly.
Step 1
Paste JSON data and a schema
Step 2
Run validation
Step 3
Review each reported path
Step 4
Fix the data or schema and validate again
How to interpret a passing result
A pass means this specific preflight did not find the issues listed above. It is not a guarantee that the target system will accept every row, field, custom mapping or account-specific rule.
A generated or passing schema is not a final data contract until optional fields, nullable values and edge cases are reviewed.