Synthetic Data Schema Regression Check
Generate mock data, derive a schema baseline, and validate subsequent synthetic runs for regressions.
Use case
Use this when building repeatable test fixtures and checking contract stability across iterations.
What to expect
Follow the steps from left to right for a quick overview, then use the inline stepper below to run each tool.
Generate mock data, derive a schema baseline, and validate subsequent synthetic runs for regressions.
Data Generator
JSON → JSON / CSV / XML / YAML
Generate mock data
Deterministic mock data generated from the requested format and count.
JSON Schema Generator
JSON → JSON-SCHEMA
Generate schema
Review the result here before moving to the next step.
JSON Schema Validator
JSON / JSON-SCHEMA → JSON
Validate schema
Validation report. The original data value is passed to the next step.
Workflow steps
Workflow shortcut
Next unlocked step: Step 1 · Data Generator
Data Generator
Generate deterministic mock records for JSON/CSV/XML/YAML testing.
Generator input (JSON envelope)
Provide { "format": "json|csv|yaml|xml", "count": number, "seed": number }.
Generated output
Deterministic mock data generated from the requested format and count.
Run this step to process the current input and prepare the next workflow stage.
JSON Schema Generator
Generate a draft JSON Schema from sample JSON input.
JSON input
Provide json input for this workflow step.
JSON-SCHEMA output
Review the result here before moving to the next step.
Run this step to process the current input and prepare the next workflow stage.
JSON Schema Validator
Validate JSON data against a provided JSON Schema.
Schema validation input
Provide { "schema": { ...jsonSchema }, "data": <value> }, or paste raw JSON to auto-validate against a generated schema.
Schema validation result
Validation report. The original data value is passed to the next step.
Run this step to process the current input and prepare the next workflow stage.