Validate Fields
AI-generatedSummary
Validate specified fields in each input item against presence, emptiness, and type constraints according to user-defined rules, annotating each item with validation results.
Inputs
- fieldRules (required) — A list of validation rules for fields. Each rule specifies a dot-path field name, whether the field is required and must be non-empty, if empty strings are allowed, and the expected data type (e.g. any, boolean, number, date, email, phone, string, or URL).
- continueOnFailure — Whether to continue workflow execution even if validation errors occur.
Output shape
a list of items, each containing the original input data with an added 'dataQuality' property detailing validation results, including a boolean 'valid' flag and an 'errors' array with error details for each failed field validation.
If validation fails and 'continueOnFailure' is false, the node throws an error stopping execution. Otherwise, the output includes validation errors per item. Outputs for each input item preserve original data and add validation metadata under 'dataQuality'. The node supports batch input and performs validation item-by-item.
Examples
Example 1: Validate customer records for required emails and phone numbers.
Define fieldRules with entries for customer.email (required, type email), customer.phone (optional, type phone), and set continueOnFailure to true to collect and report all validation errors without stopping workflow.