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name: mmlu_item_schema description: Validate and canonicalize MMLU-style four-option subject examples for evaluation workflows.

mmlu_item_schema

Use this skill when a recovery or evaluation task needs the MMLU mechanism represented by this module. Do not use it as a substitute for a full model evaluation unless the run explicitly declares a reduced proxy target.

Inputs

Inputs are JSON-compatible dictionaries following the module document contract. Required fields are validated by the script in scripts/.

Outputs

Outputs are JSON-compatible dictionaries with normalized labels, prompts, scores, or recovery artifacts. Downstream modules should consume these outputs instead of parsing free-form text.

Workflow

1. Read the paper profile and module plan to confirm the selected target.
2. Call the script or import the helper functions from scripts/.
3. Preserve the boundary between item construction, prompt construction, scoring, and recovery logging.
4. Run the validation command after changes: python <distiller>/module-to-skill/scripts/validate_skill_tree.py <skill_dir> --run-tests.

Limitations

This skill captures the evaluation mechanism, not the full hosted GPT-3 runtime or the full private benchmark distribution. Soft-mode recovery must label reduced results as proxy evidence.