divergence-detection

$npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/divergence-detection

Analyzes 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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