AWS Releases Universal Agent Evaluation Framework (UAEF) for Cross-Framework AI Agent Testing

Amazon Web Services (AWS) released the Universal Agent Evaluation Framework (UAEF) on November 11, 2026. This open-source system addresses the challenge of inconsistent evaluation standards caused by using different AI agent frameworks such as LangGraph, LangChain, Strands Agents, and Amazon Bedrock AgentCore. Previously, teams had to rebuild metrics and scoring logic for each framework's specific trace format, making it costly to switch tools or run agents on multiple platforms.

The core mechanism of UAEF involves adapters that convert execution records from various frameworks into a unified 'AgentTrace' canonical format. On this basis, the system scores agents using 36 built-in metrics across seven dimensions: tool calling, response quality, responsible AI, performance, multi-turn conversation, multi-agent coordination, and reasoning. All metrics are normalized to a [0, 1] interval, allowing agent versions from different frameworks to be compared on a single scale.

The framework also integrates personally identifiable information (PII) screening and stores results in Amazon DynamoDB and Amazon S3, enabling teams to save experiment data and generate reports. According to AWS, 12 organizations in the telecom, healthcare, and financial services industries have used UAEF to evaluate their AI agents, comparing versions before release to detect performance regressions.

UAEF is open source under the Apache 2.0 license on GitHub, providing a Python library, framework adapters, built-in metrics, and runnable notebooks. For developers building complex multi-agent systems, this tool offers a standardized evaluation infrastructure, helping to more objectively measure the impact of changes to prompts, models, or tools.