AI RESEARCH
Agentic CLEAR: Automating Multi-Level Evaluation of LLM Agents
arXiv CS.CL
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ArXi:2605.22608v1 Announce Type: new Agentic systems are becoming capable: agents define strategies, take actions, and interact with different environments. This autonomy poses serious challenges for overseeing and assessing agent behavior. Most current tools are limited, focusing on observability with basic evaluation capabilities or imposing static, hand-crafted error taxonomies that cannot adapt to new domains. To address this gap, we present Agentic CLEAR, an automatic, dynamic, and easy-to-use evaluation framework.