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multiagent-debate

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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.

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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 TypePrimary StrategyFallback Strategy
hypothesis, claimcritic-defender-judgeadversarial-escalation
research-questionmulti-perspective-panelsociety-of-mind
idea, approachsociety-of-mindcourtroom-structured
experiment-designcourtroom-structuredcritic-defender-judge
gapmulti-perspective-paneladversarial-escalation

Budget Table

ParameterS (Quick)M (Standard)L (Deep)
Debate rounds4812
Participating agents358
Coverage dimensions357
External evidence searches2510

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.

Available Strategies

Optional, no fixed order; the final leaf is always a sop.

StrategyWhen to use
adversarial-escalationStrategy: Progressive pressure escalation — starts with surface-level challenges and escalates to fundamental assumption attacks based on defender confidence decay.
courtroom-structuredStrategy: Legal adversarial structure — prosecution presents case, defense responds, evidence is cross-examined, judge delivers verdict. Emphasizes evidence quality and procedural rigor.
critic-defender-judgeStrategy: Classic triangular debate — Critic attacks, Defender responds, Judge adjudicates. Based on Irving AI Safety via Debate with Toulmin argumentation structure.
multi-perspective-panelStrategy: Multi-stakeholder review panel — diverse expert perspectives evaluate artifact simultaneously, then synthesize through structured deliberation.
society-of-mindStrategy: Multi-agent collaborative debate based on Du et al. Society of Mind. Agents share perspectives iteratively until convergence or divergence is detected.

Available Tactics

Optional, no fixed order; the final leaf is always a sop.

TacticWhen to use
evidence-tournamentTactic: Evidence gathering, cross-examination, and quality judgment. External evidence is collected, presented, challenged, and scored for relevance and reliability.
stress-test-dialectical-escalationTactic: Progressive debate escalation based on confidence thresholds. Each round increases attack sophistication until defender collapses or proves resilient.
stress-test-perspective-rotationTactic: Sequential perspective evaluation with divergence aggregation. Each agent evaluates from a distinct viewpoint, then disagreements are surfaced and resolved.

Available SOPs

Optional, no fixed order; the final leaf is always a sop.

SOPWhen to use
context-checkpointAppend research process and results to the current Phase's context file. Each append MUST contain >=500 lines of markdown covering both process and results. Use this skill at plan-designated checkpoint points — typically after each strategy completes or at key decision nodes within a research Phase.
context-initCreate a new context file for a research Phase. Called once at Phase start to initialize the file that subsequent context-checkpoint calls will append to. Use this skill whenever a new research Phase begins and a fresh context file is needed.
debate-transcript-analysisExtracts key turning points, patterns, and insights from completed debate transcripts. Produces structured summary for verdict synthesis.
stress-test-saturation-detectionDetermines whether validation has reached saturation — no new weaknesses or failure modes being discovered. Used by all 5 campaigns as termination signal.
verdict-synthesisSynthesizes findings from a completed campaign into typed verdict reports. Produces DebateVerdict, RedTeamReport, FailureAnticipationReport, CounterfactualMap, or AdversarialStressReport depending on campaign. Also supports cross-campaign StressTestSummary.
weakness-classificationClassifies discovered weaknesses into severity tiers (fatal/major/minor/cosmetic) with structured justification and exploitability assessment.