data-labeling
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claude
model-evaluation
Model evaluation: metrics with confidence intervals, calibration, sliced and fairness evaluation, and LLM output quality.
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Plugin model-evaluation from marketplace libre-mlops in HermeticOrmus/LibreMLOps-Claude-Code. Commands read from the repo's manifest — 1 month ago.
What it installs
Skills (1)
model-evaluation-patternsModel evaluation patterns with code: a complete classification report, calibration analysis, sliced evaluation, fairness metrics, and LLM evaluation with BERTScore and RAGAS. Use when deciding whether a model is good enough to ship.
Slash commands (1)
/model-evaluation:evaluate-modelCompute classification metrics with confidence intervals, fairness across subgroups, calibration, or a statistical comparison of two model versions.
Subagents (1)
model-evaluatorUse this agent when a model needs evaluating beyond one accuracy number: classification metrics with confidence intervals, calibration, per-subgroup slices, fairness with Fairlearn or AI Fairness 360, cost-sensitive thresholds, or LLM output quality with BLEU, ROUGE, BERTScore, or G-Eval.
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