Impatient Users Confuse AI Agents: High-fidelity Simulations of Human Traits for Testing Agents

The paper introduces TraitBasis, a model-agnostic framework for stress testing AI agents by simulating user traits like impatience and incoherence without requiring fine-tuning or additional data. It extends the existing $\tau$-Bench to $\tau$-Trait, revealing a performance degradation of 2%-30% across frontier models when subjected to altered user behaviors. This approach emphasizes the importance of robustness testing in AI systems, providing practitioners with a tool to enhance the reliability of agents in real-world interactions.