AWS has introduced the Universal Agent Evaluation Framework, or UAEF, to give teams one way to test AI agents built with different software frameworks. Adapters convert messages, tool calls and agent handoffs into a common trace before scoring, so a change of framework does not require a new evaluation system.
UAEF includes 36 metrics across seven dimensions, covering areas such as tool use, response quality, safety, performance, multi-turn conversations and multi-agent coordination. It can test an agent against a prepared dataset or normalize traces from previous runs. Ground-truth answers are optional, though tests of tool calling need expected tools, order and arguments.
The framework screens traces for personal information before storing experiment metadata in DynamoDB and full results in S3. Teams can then compare a new prompt, model or tool set with a baseline and inspect what improved or regressed. AWS says customers from 12 organizations in telecom, healthcare and financial services used UAEF, but the announcement describes a testing workflow rather than evidence that any particular agent became more accurate.