Skip to content
Back to skills

Disagreement Mapping

ASecurity

Map disagreement structure by collecting judgments, clustering opinions, extracting arguments per cluster, and visualizing fault lines.

  • 417 stars
  • 0 votes
  • 0 copies
  • 0 views
  • Added June 1, 2026
research

Security analysis

A100/100

Scanned June 1, 2026

npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill disagreement-mapping --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Disagreement Mapping?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Disagreement Mapping
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/yogsoth-ai-disagreement-mapping/badge)](https://www.skillsdirectory.com/skills/yogsoth-ai-disagreement-mapping)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: disagreement-mapping
description: Map disagreement structure by collecting judgments, clustering opinions, extracting arguments per cluster, and visualizing fault lines.
execution: tactic
used-by: structured-consensus
---

# Disagreement Mapping

Map the structure of disagreement rather than forcing convergence. Collect diverse judgments, identify natural clusters of opinion, extract the core arguments supporting each cluster, and produce a visual map of the disagreement topology.

## Stages

1. **Collect** — Run `judgment-collection` to gather positions and reasoning from all perspectives
2. **Cluster** — Run `cluster-analysis` to identify natural groupings of similar positions
3. **Extract** — Run `argument-extraction` for each cluster to surface core arguments
4. **Visualize** — Run `disagreement-visualization` to produce the disagreement map

## Available SOPs

| SOP | Role in Tactic |
|-----|---------------|
| judgment-collection | Gather positions with reasoning from all perspectives |
| cluster-analysis | Identify natural opinion clusters and characterize them |
| argument-extraction | Extract and steel-man core arguments for each cluster |
| disagreement-visualization | Produce structured map of clusters, arguments, and fault lines |

## Execution Guidance

- Collect BOTH positions AND reasoning (not just ratings)
- Clustering should be based on reasoning similarity, not just position proximity
- Each cluster's arguments should be steel-manned (strongest possible version)
- Visualization should show: cluster sizes, key arguments, fault lines between clusters
- Identify whether disagreements are empirical, value-based, or definitional

## Minimum Yield

- Disagreement clusters (identified clusters with characterization)
- Core arguments per cluster (core arguments per cluster, steel-manned)
- Visualization (disagreement map showing topology and fault lines)

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…