evaluator-optimizer

An evaluator-optimizer feedback loop is a multi-agent architecture pairing a generator and an evaluator to progressively enhance output quality through iterative improvement rounds.

Iterative refinement improves code reviews and API design by running an initial draft through dual agents that score outputs against explicit thresholds over multiple rounds until quality criteria are met.

Yes, automated quality assurance supports explicit max-iteration limits and scoring thresholds to govern the generator-evaluator loop, returning the best-attempt output if thresholds are not reached.

Automating documentation refinement is best handled by a dual-agent architecture where independent tools handle generation and evaluation, applying multi-round scoring to iteratively improve complex drafts.

The generator-evaluator pattern works without external dependencies, using independent tools within the dual-agent architecture to execute the iterative improvement workflow and return refined outputs.

Iterative improvement for algorithm optimization should be avoided when strict max-iteration limits cannot accommodate the required multi-round refinement cycles, returning only a best-attempt result instead.