divergence-detection
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npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/divergence-detectionAnalyzes agreement and disagreement patterns across perspectives
- Tracks consensus and persistent divergence in multi-perspective evaluations
- Uses perspective outputs and round number from multiagent-debate
- Maps clusters of agreement and identifies irreconcilable issues
- Returns structured analysis for use in subsequent deliberation rounds
SKILL.md
.github/skills/divergence-detectionView on GitHub ↗
--- name: divergence-detection description: Identifies agreement and disagreement patterns across multiple perspective evaluations. Maps consensus clusters and persistent divergence points. execution: subagent prompt: ./prompt.md input: perspective_outputs (string), round_number (string) used-by: [multiagent-debate] --- # Divergence Detection Identifies agreement/disagreement across perspectives. ## Execution Subagent — spawned via subagent-spawning/spawn-agent. ## Why Subagent Divergence analysis requires comparing all perspective outputs simultaneously in dedicated context without being anchored to any single perspective. ## Input - **perspective_outputs**: All perspective-critic outputs from current round - **round_number**: Current deliberation round (for tracking convergence trend) ## Output - **consensus_points**: Issues where >70% of perspectives agree - **divergence_points**: Issues where >50% of perspectives disagree - **convergence_trend**: Whether disagreements are shrinking, stable, or growing - **irreconcilable**: Points unlikely to resolve through further deliberation ## Budget One unit = one divergence analysis per round.
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