Microsoft Open Sources Evals for Agent Interop Starter Kit to Benchmark Enterprise AI Agents

"Enterprises building autonomous agents powered by large language models face new challenges that traditional test approaches were not designed to address. Agents behave probabilistically, integrate deeply with applications, and coordinate across tools, making isolated accuracy metrics insufficient for understanding real-world performance."

"The Evals for Agent Interop starter kit aims to give teams a repeatable, transparent evaluation baseline. It ships with templated, declarative evaluation specs in form of JSON files and a harness that measures signals such as schema adherence and tool call correctness alongside calibrated AI judge assessments for qualities like coherence and helpfulness."

"Microsoft also includes a leaderboard concept in the starter kit to provide comparative insights across strawman agents built using different stacks and model variants. This helps organizations understand relative performance across different implementation approaches."

Microsoft introduced Evals for Agent Interop, an open-source starter kit addressing the challenge of evaluating AI agents in enterprise environments. Traditional testing methods prove inadequate for probabilistic agents that integrate deeply with applications and coordinate across multiple tools. The kit provides curated scenarios, representative datasets, and an evaluation harness measuring schema adherence, tool call correctness, and AI judge assessments for coherence and helpfulness. It includes templated JSON-based evaluation specifications and a leaderboard comparing strawman agents built with different stacks and model variants. Initially focused on email and calendar interactions, the toolkit is designed for expansion with enhanced scoring capabilities and broader workflow support.

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