A Simple Framework for Evaluating AI-Generated Responses

This paper presents a lightweight evaluation framework for assessing AI-generated responses using three core qualitative criteria: relevance, accuracy, and clarity. As AI systems become increasingly integrated into academic, professional, and creative workflows, the need for systematic evaluation methods has grown. The proposed framework offers a structured yet accessible approach for scoring and interpreting AI outputs. A practical example from the film industry demonstrates its application. The framework supports consistent evaluation, highlights common performance patterns, and provides a foundation for iterative improvement in both AI systems and human-in-the-loop processes.