# Divergence Detection

> Identifies agreement and disagreement patterns across multiple perspective evaluations. Maps consensus clusters and persistent divergence points.

- Skill: `yogsoth-ai/divergence-detection` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add yogsoth-ai/divergence-detection`
- Raw SKILL.md: https://api.skillmd.com/api/skills/yogsoth-ai/divergence-detection/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: yogsoth-ai (https://skillmd.com/u/yogsoth-ai)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/yogsoth-ai/divergence-detection

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# 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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## Available SOPs

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

| SOP | When to use |
| --- | --- |
| spawn-agent | Spawn a customized CC subagent with full MCP tool access. Used by SOPs that declare execution: subagent. |

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