LLM Output Schema Validator
Paste model responses and a JSON schema and see which validate, which fail and why, including the code fences, wrapper text, trailing commas and type coercions that break structured output in production.
Last reviewed by the Radiatus Cloud team
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Structured output fails in a small number of predictable ways
A model asked for JSON returns valid JSON almost always, and the failures cluster: a markdown code fence around the object, a sentence of explanation before it, a trailing comma, single quotes instead of double, a number written as a string, or an enum value that is a plausible synonym of one you listed. Each of these is trivially detectable and repairable, and each throws an unhandled exception in a parser that assumed success. Validating at the boundary turns an outage into a retry.
The schema is also a prompt
Field names and enum values do more work than the instructions around them, because the model reads the schema as a description of what is wanted. A field called x1 with no description will be filled with something; a field called confidence_0_to_1 with its range in the name will be filled with something closer to what you meant. Renaming fields to be self-describing is usually the cheapest accuracy improvement available in a structured-output pipeline, and it costs one deployment.
Validation is not verification
An output can satisfy every constraint in the schema and be entirely wrong. Types, required fields and enum membership are cheap to check and catch the failures that crash code; they say nothing about whether the extracted value is the right one. A pipeline that validates the schema and stops has confirmed the shape of the answer, which is worth doing and is not the same as confirming the answer.
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Frequently Asked Questions
What are the most common structured-output failures?
A markdown fence around the object, explanatory text before or after it, trailing commas, single quotes, numbers emitted as strings, and enum values that are plausible synonyms of the ones you listed.
Should I repair malformed output or retry?
Repair the deterministic failures such as fences and trailing commas, since a retry costs a full round trip to fix something the client can fix locally. Retry when the structure is genuinely wrong rather than merely wrapped.
Why do field names matter?
Because the model reads the schema as a description of what is wanted. A field called confidence_0_to_1 produces better values than one called x1, and renaming is usually the cheapest accuracy improvement available.
Does schema validation mean the output is correct?
No. An output can satisfy every constraint and be entirely wrong. Validation confirms the shape of the answer, which is not the same as confirming the answer.
Does this implement all of JSON Schema?
No, a common subset. Constructs it does not implement, such as oneOf, allOf and format, are ignored rather than enforced, so a pass here does not imply a pass under a full validator.
Privacy & Security
Everything runs in your browser; nothing is uploaded.
How to Use
Paste your schema and one or more model outputs to validate them.
Disclaimer: This tool is provided "as is" without warranty of any kind. Results are for educational and utility purposes.
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