metric-design — Decomposed, Multi-Criteria Metrics for LLM Pipelines

"It's unproductive to launch optimization runs using a poorly designed program or a bad metric." — DSPy core team [dspy.ai/learn/optimization/overview/]

"LLM judges exhibit self-preference, recency, rubric-order, score-ID, and length biases." — Synthesized from [arxiv.org/pdf/2506.02592, arxiv.org/pdf/2509.26072]

This is a tool skill. It produces a metric function (and a calibration receipt) that other skills consume — DSPy compilers (MIPROv2 / GEPA / BootstrapFewShot), LlamaIndex FaithfulnessEvaluator/RelevancyEvaluator/RetrieverEvaluator, LangGraph eval judges, RAGAS, TruLens. The metric is the optimization target. Get it wrong and every downstream optimizer is theatre.

1. 何时激活 (When to Activate)

Activate when any of these is true: