How to Regression-Test the Systems Evaluating Your AI Agents
An agent is supposed to call lookup_order, then issue_refund, then explain the result. The trace shows exactly that sequence. The evaluation dashboard marks the run as a failure: “required tool missing.”
After an hour of prompt changes, someone inspects the adapter. It renamed issue_refund to refund during normalization, while the contract still expected the original name.
The agent was not failing. The measurement system was. This is a synthetic example, but I encounter the design problem often while maintaining AgentInspect, an open-source local evidence debugger for TypeScript agents. I maintain AgentInspect; it is used here as one concrete implementation of the broader pattern. The argument does not depend on using that library.
Agent evaluations are software. Their parsers, adapters, rubrics, joins, fixtures, and graders can regress. Treating the resulting score as ground truth without testing the evaluator creates a dangerous feedback loop: teams “improve” the agent until it satisfies a...
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