InFlowOp uses one label-free cost to set both task decomposition and fault repair, gaining up to 11.97% over a single agent on Braid
The work proposes InFlowOp, which prices every decision in one label-free cost that weighs how well an agent's competence meets a subtask's demands against how much that agent takes to run, using it before execution to bidirectionally set decomposition granularity and agent assignment and during execution to locate and locally correct faults, and introduces Braid, a benchmark whose tasks require multi-agent coordination, reporting gains up to +11.97% over single-agent baselines across eight domains and six backbones, with +9.64% from in-flow optimization.