<p>Conflict phenomena are ubiquitous in human society, and conflict analysis models have been extensively studied. However, the differences between rough set-based conflict analysis and clustering methods have not been clearly clarified, leading to the absence of effective evaluation criteria for rough set-based conflict analysis. To address this issue, this paper develops novel evaluation criteria for three-way conflict analysis by integrating its characteristics and drawing on classical clustering evaluation indices. First, we clarify the essential differences between rough set-based conflict analysis and clustering from three key perspectives. Second, we propose four new evaluation indices to quantitatively assess the quality of three-way conflict analysis results. Third, based on these criteria, we construct a universal three-way conflict analysis framework that can improve final decision performance without modifying the original conflict model. The main findings show that the proposed indices can effectively evaluate conflict results, and the universal framework exhibits strong generality and transferability across different models. Case studies are provided to validate the effectiveness of the evaluation criteria and the practicability of the proposed framework.</p>