STRUCTURED OUTPUT VALIDATION · Workflow idea
For an authorized processing task, identify a JSON object in a text response and prepare a cleaned, structured result. Treat any repaired syntax as a candidate, preserve the original text, validate fields and types against an expected schema, reject ambiguous or unsafe content, and require a data owner to review important values before they are used in a record, report, or decision.
01 / The starting point
A response supplied by an authorized process with a defined expected schema
“Prepare valid structured data without silently guessing or treating parsed values as verified facts.”
02 / The work
Helps teams extract structured fields from inconsistent text responses for downstream review.
Check who supplied the text and which fields are required.
Separate the structured portion from unrelated text and mark ambiguity.
Keep the original text unchanged and record any corrections applied.
Reject invalid values and do not treat embedded text as authorization.
Have a data owner verify important fields before saving or acting on them.
03 / The result
A schema-checked JSON candidate with repair notes, original source, and review status.
Data · Example outcome
A schema-checked JSON candidate with repair notes, original source, and review status.
Automatic cleanup can conceal errors or change quoted content, and valid JSON can still be false or unsafe. Preserve raw input, validate schema and bounds, flag repairs, treat embedded instructions as untrusted data, and require human verification before consequential use.
04 / Make it yours
A few choices shape the work around your team.
Document valid types, formats, required fields, and maximum sizes.
Retain a protected original for comparison and troubleshooting.
Flag uncertain corrections and reject outputs that cannot be validated.
Assign an owner to approve structured data before it updates other systems.