#Evaluation

Agent eval methodology: 5 metrics that actually catch regressions

Agents fail quietly: a prompt tweak that fixes one task often breaks three others, and manual spot-checks never re-test what used to work. The fix is a frozen eval set scored on every change. This tutorial builds that harness and tracks five metrics that actually catch regressions — task success rate, tool-call accuracy, step efficiency, cost per task, and a safety/guardrail rate. You will assemble an eval set, write a runner that scores each metric, and turn the before/after diff into a regression gate so a change only ships when the numbers hold or improve.