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Paper · arXiv

Agentic CLEAR: Automating Multi-Level Evaluation of LLM Agents

Agentic systems are becoming more 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. It produces textual insights into the agent behavior on three levels of granularity: system, trace, and node. Agentic CLEAR operates above the observability layer, enabling seamless integration and featu...

AuthorsAsaf Yehudai, Lilach Eden, Michal Shmueli-Scheuer
Primary categorycs.CL
Published21 May 2026
Last updated at source21 May 2026
cs.CLcs.AI
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