evaluation

To evaluate agent performance using rubrics, apply a multi-dimensional rubric engine to score non-deterministic outputs across factual accuracy, completeness, citation accuracy, source quality, and tool efficiency with weighted scoring.

Rubric-driven evaluation for production monitoring is the process of applying automated scoring pipelines and test-set management to agent deployments, which flags performance regressions and guides improvements during live operations.

Compare agent configurations by running automated evaluation cycles against a managed test-set, yielding weighted rubric-based scores that highlight behavioral differences across non-deterministic paths and context strategies.

Yes, you can use this evaluation framework for research, development, and production monitoring contexts to measure, compare, and improve agent behavior using scalable, repeatable validation pipelines.

An agent evaluation rubric should include factual accuracy, completeness, citation accuracy, source quality, and tool efficiency dimensions, applying weighted scoring to measure multi-dimensional agent behavior comprehensively.

No external dependencies are required to run evaluation pipelines; the skill operates independently using its internal scripts and references to manage test-sets and generate rubric-based scores.