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This paper demonstrates that counterfactual fairness audits of multi-step clinical LLM agents require measuring per-action instability floors to interpret flip rates accurately, as inherent heterogeneity can mask demographic disparities.
MARGINAL is an open-source governance layer for coding agents that monitors agent trajectories to prevent inefficient actions, with features like shadow mode and earned enforcement to improve reliability.