multi-level-agent-evaluation-3f2a14fc·1 events·first seen Aliases: multi-level agent evaluation
Agentic CLEAR is an automatic evaluation framework for LLM-based agentic systems that analyzes behavior at three granularity levels: system, trace, and node. Unlike existing tools that rely on static error taxonomies or focus only on observability, it dynamically generates textual insights and integrates above the observability layer with an accessible UI. Experiments across four benchmarks and seven agentic settings demonstrate strong alignment with human-annotated errors and predictive accuracy for task success rates.