multiagent-debate
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npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/multiagent-debateCore question: **Can this artifact survive structured adversarial debate?**
SKILL.md
.github/skills/multiagent-debateView on GitHub ↗
--- name: multiagent-debate description: "Campaign: Multi-agent structured debate for adversarial validation. Core question: Can this artifact survive structured adversarial debate? Methods: Irving AI Safety via Debate, Du Society of Mind, Liang MAD, Toulmin Argumentation, D3 framework." type: campaign produces: DebateVerdict artifact-types: [gap, hypothesis, research-question, idea, approach, experiment-design, claim] --- # Multi-Agent Debate Campaign Core question: **Can this artifact survive structured adversarial debate?** ## Methodology Sources - Irving et al. (2018) — AI Safety via Debate - Du et al. (2023) — Society of Mind multi-agent sharing - Liang et al. (2023) — MAD (Multi-Agent Debate) - Toulmin (1958) — Argumentation model (claim, ground, warrant, backing, qualifier, rebuttal) - D3 framework — Deliberate, Debate, Decide ## Strategy Routing | Artifact Type | Primary Strategy | Fallback Strategy | |---|---|---| | hypothesis, claim | critic-defender-judge | adversarial-escalation | | research-question | multi-perspective-panel | society-of-mind | | idea, approach | society-of-mind | courtroom-structured | | experiment-design | courtroom-structured | critic-defender-judge | | gap | multi-perspective-panel | adversarial-escalation | ## Budget Table | Parameter | S (Quick) | M (Standard) | L (Deep) | |---|---|---|---| | Debate rounds | 4 | 8 | 12 | | Participating agents | 3 | 5 | 8 | | Coverage dimensions | 3 | 5 | 7 | | External evidence searches | 2 | 5 | 10 | ## Tactics - **dialectical-escalation** — Progressive pressure escalation based on confidence thresholds - **perspective-rotation** — Sequential perspective evaluation with divergence aggregation - **evidence-tournament** — Evidence gathering, cross-examination, and quality judgment ## Context Management Each subagent operates in isolated context. The debate-architect designs structure before execution. Transcripts are passed between rounds via structured markdown. Saturation detection terminates when novelty drops below threshold. ## Output Produces `DebateVerdict` containing: survival assessment, key vulnerabilities, confidence score, debate transcript summary, and recommended mitigations.