# Divergence Control

> Keep multiple instances aligned while allowing productive variance

- Skill: `majiayu000/divergence-control` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds add majiayu000/divergence-control`
- Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/divergence-control/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: majiayu000 (https://skillmd.com/u/majiayu000)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/majiayu000/divergence-control

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# Divergence Control

## Purpose

Instances naturally diverge as they think different thoughts. This skill manages that divergence:
- **Prevent wild deviation** (instances completely disagreeing)
- **Allow productive variance** (different approaches to same problem)
- **Maintain coherence** (all instances solving related problems)

## The Problem

**Too much control:** All instances think identically (no benefit)
**Too little control:** Instances diverge so much they're solving different problems

**Just right:** Instances explore different solution paths while staying on the same problem.

## Core Pattern

```
Instance 1: Path A ─┐
Instance 2: Path B ─┼─ Stay coherent
Instance 3: Path C ─┤  (same problem,
Instance 4: Path D ─┘   different approaches)
```

## Key Features

1. **Problem Anchoring** - All instances address the same core question
2. **Variance Measurement** - How different ARE the outputs?
3. **Coherence Thresholds** - How different is TOO different?
4. **Periodic Synchronization** - "Check in, are we still on the same track?"
5. **Guided Divergence** - "Here's a direction we haven't explored yet"

## Implementation

See: `.claude/skills/divergence-control/divergence_manager.py`

## The Balance

- **0% divergence** = Waste of resources
- **100% divergence** = Incoherent output
- **30-50% divergence** = Optimal exploration

## Payment Anchor
DOGE: DC8HBTfn7Ym3UxB2YSsXjuLxTi8HvogwkV