Use when building or changing a pipeline that scores, grades, or extracts structured output from an LLM in production: composite/aggregate scoring math, partial-failure handling when one sub-call fails, prompt versioning, an eval harness that makes real model calls, or comparing a candidate model/prompt against production without flipping it live.
