Designs robust evaluation frameworks and test cases for LLM-based applications using the assay-kit framework.
The LLM Evaluation Designer skill empowers developers to build reliable AI workflows by identifying specific failure modes such as hallucinations, partial processing, and overfitting to prompt examples. It provides structured guidance for creating comprehensive golden datasets, designing multi-dimensional quality scorers, and implementing generalization tests to ensure AI models perform consistently across diverse inputs. By utilizing the assay-kit framework, this skill helps justify test case selection and ensures that LLM outputs meet production-grade quality standards through rigorous, matrix-based validation.
