Guide-linked quiz · Medium Level
Structured Outputs Quiz
Test schema-required fields, nulls, extra properties, arithmetic and source checks, refusals, versioning, and why valid JSON can still be wrong.
Question 1 of 8
A JSON Schema declares a property named total. What must also be specified if every response must include it?
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- A JSON Schema declares a property named total. What must also be specified if every response must include it?
- Set its numeric type only
- Add total to the required-field list
- Place it first in the schema file
- Give the object a longer description
- Why decide whether additional object fields are allowed?
- Any extra property always proves hallucination
- JSON syntax forbids all additional properties
- Only arrays can contain unexpected fields
- Unexpected fields can change how downstream code interprets a response
- A missing value and an explicit null have different meanings in an integration. What should the schema specify?
- Their separate allowed behavior and downstream interpretation
- Treat absence and null as the same without documentation
- Replace both with a fabricated zero
- Let every provider choose silently
- A receipt has subtotal 50 and tax 5; valid JSON reports total 550. What failed?
- JSON parsing
- The total field’s numeric type
- Factual and arithmetic validation against the source
- The existence of an object schema
- A structured result cites source_id 9, but only IDs 1 through 3 were supplied. What check catches the error?
- Check that source_id is a string
- Count the object’s top-level keys
- Accept any integer because its type is valid
- Verify that referenced identifiers actually exist in the supplied evidence
- How should an application handle a model refusal or truncated response?
- Assume every schema field was produced
- Treat it as an explicit non-success case rather than inventing required values
- Silently fill missing evidence with plausible defaults
- Ignore the boundary because JSON mode was requested
- A stored output uses schema v1 but a consumer expects v2. What should the integration do?
- Apply v2 assumptions without checking
- Remove the version field
- Reject or explicitly adapt the incompatible version
- Assume schema changes affect only formatting
- Two providers offer structured output, one constrains generation and one validates afterward. Which practice remains necessary for both?
- Check supported schema features and verify the values’ meaning
- Assume identical enforcement for every schema keyword
- Skip factual checks when output parses
- Treat post-validation as a guarantee of truth
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