Evaluator-Optimizer

In depth

An agent workflow where one LLM call writes a response and a second call checks it against explicit criteria and sends back feedback. The two repeat until the output passes or a stop condition is hit. Anthropic lists it as a core agentic workflow and says it works best when the evaluation criteria are clear, as in literary translation where a critic catches nuances the first draft missed. Unlike self-reflection, the critic is a separate prompt or model, and a maximum iteration count stops the loop from running forever.

Primary source: anthropic.com