UAEF: A framework-agnostic system for closed-loop evaluation of AI agents
TL;DR
The Universal Agent Evaluation Framework (UAEF) is a framework-agnostic system for evaluating AI agents. UAEF converts each framework's traces into one canonical format, scores them with 36 built-in metrics across 7 dimensions, and stores results so teams can compare agent versions and catch regressions.
Nauti's Take
The evidence base is still narrow because the available source is the AWS Machine Learning Blog; metric definitions, reference scores, and the effort required for trace normalization remain unclear. A small team should test UAEF against its own regression set and a few critical workflows before adopting it as an evaluation standard.
Sources
10.11.26
