Stringified JSON Field Normalizer with Per-Record Status Card

How it works

1. 1.Manual Trigger starts the run.
2. 2.Mixed Sample Payload emits three fictional records: a real object, valid JSON strings and one truncated JSON string.
3. 3.Normalize JSON Fields walks fields recursively up to depth 8 and tags each as was_object, parsed_from_string, remained_string or corrupt.
4. 4.Detection is prefix-based, so truncated JSON is attempted and reported corrupt instead of passing as plain text.
5. 5.IF checks _normalization.has_corrupt and routes clean records to true, corrupt ones to false, each via a NoOp.
6. 6.Merge append with two separate inputs, then Build Status Cards emits one status card per record.

Use cases

• Normalizing payloads where the same field arrives sometimes as object, sometimes as a JSON string.
• Detecting unparsable or truncated string fields before downstream nodes break.
• Producing a diagnostic report of which field paths were parsed from strings.
• Cleaning database rows that store JSON inside text columns.

Requirements

• n8n version matching the listed node typeVersions (2.47.x).
• No credentials required; the workflow is fully local.
• For production data, replace the sample Code node with your own source emitting the same item shape.

Setup and testing in n8n

1. Import the JSON and click Execute Workflow.
2. Verify REC-001 and REC-003 return status normalized and REC-002 returns has_corrupt_fields with corrupt_fields=["meta"].
3. Verify REC-001 meta is now an object and meta.source is reachable.
4. Edge case: make the sample node return an empty array; the run finishes without errors.
5. Edge case: add a string field like '[1,2' and confirm it is tagged corrupt without stopping execution.

Service Value

Ready-made workflow template for automation delivery and service execution.