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Glossary · Workflow design

JSON schema

Also called: JSON Schema validation, schema

JSON Schema is a standard vocabulary for describing what a JSON document must look like (which fields are required, their types, formats, allowed values and ranges) so data can be validated automatically.

A schema is a contract. This one says an invoice must have a vendor, a positive total and an ISO date:

{
  "type": "object",
  "required": ["vendor", "total", "due_date"],
  "properties": {
    "vendor": { "type": "string", "minLength": 1 },
    "total": { "type": "number", "exclusiveMinimum": 0 },
    "due_date": { "type": "string", "format": "date" },
    "po_number": { "type": "string" }
  }
}

A validator compares data against it and returns either "valid" or a list of exactly what's wrong.

Where it earns its keep in automation

  • After AI steps. Language models are good at following a format and occasionally bad at it. A schema check turns "occasionally" into a routed exception instead of a corrupted record. See structured output.
  • At webhook boundaries. Validate incoming payloads before anything acts on them; a sender's format change becomes a clear failure, not silent bad data.
  • Between workflows. A sub-workflow's inputs are an API contract; a schema documents and enforces it.

Keep schemas honest

Only mark fields required if the downstream step truly needs them. Over-strict schemas push people to make models invent values, which is worse than an empty field.

In Fluxo Flow

The Validator node checks data against simple rules ("email exists", "amount greater than 0") or a JSON schema, then routes the run to a pass or fail branch. Put it right after AI steps and right before actions that write to other systems.

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