evaluation

Agent performance evaluation for non-deterministic workflows uses a structured rubric and repeatable test sets to measure factual accuracy, completeness, citation quality, and tool efficiency. This approach ensures repeatable benchmarking and regression detection across variable agent outputs.

Rubric-based evaluation is a method that scores agent outputs against predefined criteria like factual accuracy, source credibility, and tool efficiency. It provides a structured engine to systematically assess non-deterministic agent workflows instead of relying on manual review.

Test set management for agent benchmarking involves curating repeatable input scenarios and running them through an evaluation engine to generate baseline scores. Comparing subsequent runs against these baselines enables systematic regression detection.

Production monitoring hooks can sample real agent interactions in live environments to trigger alerts and prevent regressions. They integrate with your evaluation framework to continuously assess agent quality against your configured rubrics.

Agent evaluation applies directly to tool orchestration and context strategies by assessing tool efficiency within the rubric. It measures how well the agent selects and executes tools and manages context under non-deterministic conditions.