Structured Evaluation Framework With Standardized Rubrics

via “llm-as-judge evaluation with configurable scoring rubrics”

AI testing for quality, safety, compliance — vulnerability scanning, bias/toxicity detection.

Unique: Uses a separate LLM as an evaluator with configurable scoring rubrics that define criteria, scale, and examples, enabling semantic evaluation of subjective qualities. The framework abstracts the judge LLM behind a consistent interface, enabling judge model swapping and comparison.

vs others: More flexible than metric-based evaluation (BLEU, ROUGE) because it can evaluate semantic qualities like faithfulness and harmfulness that aren't captured by surface-level metrics, and more scalable than human annotation because it automates scoring at LLM API cost.