society-of-mind

Agent Building

Strategy: Multi-agent collaborative debate based on Du et al. Society of Mind. Agents share perspectives iteratively until convergence or divergence is detected.

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Source SKILL.md: https://github.com/yogsoth-ai/de-anthropocentric-research-engine/blob/HEAD/skills/society-of-mind/SKILL.md

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Society of Mind Strategy

Multiple agents evaluate independently, then share and revise through iterative rounds.

Method

debate-architect assigns N distinct perspectives to agents
Each perspective-critic evaluates artifact from assigned viewpoint
All perspectives shared — agents revise positions given others' arguments
divergence-detection identifies agreement clusters and persistent disagreements
Repeat sharing rounds until convergence or saturation

Budget Table

Parameter	S	M	L
Debate rounds	4	8	12
Participating agents	3	5	8
Coverage dimensions	3	5	7
External evidence searches	2	5	10

Orchestration

debate-architect → [assign perspectives]
→ [parallel]: perspective-critic × N
→ [for each sharing round]:
    share all outputs → perspective-critic revises
    → divergence-detection → (converge or continue)
→ debate-transcript-analysis → verdict-synthesis

Subagents

debate-architect (perspective assignment)
perspective-critic × N (perspective evaluation)
divergence-detection (convergence tracking)
confidence-calibration (termination decision)

Available Tactics

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

Tactic	When to use
stress-test-perspective-rotation	Tactic: 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.

SOP	When to use
confidence-calibration	Calibrates confidence scores based on debate progression. Determines whether to escalate, continue, or terminate based on cumulative evidence.
debate-architect	Designs debate structure based on artifact type — selects attack vectors, assigns perspectives, determines escalation ladder, and configures round parameters.
divergence-detection	Identifies agreement and disagreement patterns across multiple perspective evaluations. Maps consensus clusters and persistent divergence points.
perspective-critic	Evaluates artifact from a specific assigned perspective. Produces assessment grounded in that viewpoint's values, priorities, and expertise.