Simulated user agents are increasingly used in usability testing to support fast, iterative UX workflows, as they generate rich data such as action logs and think-aloud reasoning, but the unstructured nature of this output often obscures actionable insights. We present UXCascade, an interactive tool for extracting, aggregating, and presenting agent-generated usability feedback at scale. Our core contribution is a multi-level analysis workflow that (1) highlights patterns across persona traits, goals, and outcomes, (2) links agent reasoning to specific issues, and (3) supports actionable design improvements. UXCascade operationalizes this approach by listing agent goals, traits, and issues in a structured overview. Practitioners can explore detailed reasoning traces and annotated views, propose interface edits, and assess their impact across personas. This enables a top-down, exploration-driven analysis from patterns to concrete UX interventions. A user study with eight UX professionals demonstrates that UXCascade integrates into existing workflows, enabling iterative feedback during early-stage interface development.

翻译：模拟用户代理在可用性测试中的应用日益广泛，以支持快速、迭代式的用户体验工作流程，因为它们能生成丰富的输出数据，如操作日志和出声思考推理。然而，这类输出的非结构化特性常常掩盖了可操作的洞察。我们提出了UXCascade，这是一个用于大规模提取、聚合和呈现代理生成的可用性反馈的交互式工具。我们的核心贡献是一个多层次分析工作流程，它能够：(1) 突显跨人物角色特征、目标和结果的模式，(2) 将代理推理与具体问题关联起来，(3) 支持可操作的设计改进。UXCascade通过以结构化概览形式列出代理目标、特征和问题，实现了这一方法。从业者可以探索详细的推理轨迹和带注释的视图，提出界面修改建议，并评估这些修改对不同人物角色的影响。这使得一种自上而下、由探索驱动的分析成为可能，即从模式识别到具体的用户体验干预。一项涉及八位用户体验专业人员的用户研究表明，UXCascade能够融入现有的工作流程，在早期界面开发阶段实现迭代式反馈。