Stop Ranking Agent Configs by Average Score

Best-worst comparisons and Plackett-Luce utility scores provide a cleaner method for evaluating agent configurations than average-score leaderboards. The approach uses MaxDiff-style judging where a model selects only the best and worst outputs per batch. This reveals interaction effects between model, prompt, and tool choices that isolated scoring misses.