> For the complete documentation index, see [llms.txt](https://docs.layerlens.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.layerlens.ai/more-in-this-section-6/score-structured-output.md).

# Recipe: score a structured-output prompt

For structured-output evaluation (JSON, fields, schemas), the canonical samples are:

* [`samples/modalities/document_evaluation.py`](https://github.com/layerlens/stratix-python/blob/main/samples/modalities/document_evaluation.py) — extraction accuracy, cross-field consistency, structural integrity
* [`samples/core/judge_creation_and_test.py`](https://github.com/layerlens/stratix-python/blob/main/samples/core/judge_creation_and_test.py) — build a custom judge that validates structured output against rules

## Pattern

Define a judge with `client.judges.create(name=, evaluation_goal=)` whose rubric encodes your schema requirements. Run on traces via `client.trace_evaluations.create(trace_id=, judge_id=)`.

For deterministic JSON-schema validation specifically, validate client-side before posting traces — that catches shape errors before consuming an evaluation.

## See also

* [Concept: Scorers](/8.-evaluate-score-the-outputs/scorers-1.md)
* [Stratix Premium — Scorers](/8.-evaluate-score-the-outputs/scorers.md)


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