Identify natural opinion clusters from collected judgments and characterize each cluster.
Scanned 6/1/2026
Install to Claude Code
Skills Directorynpx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill cluster-analysis --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: cluster-analysis
description: Identify natural opinion clusters from collected judgments and characterize each cluster.
execution: subagent
prompt: ./prompt.md
input: judgments[]
used-by: structured-consensus
---
# Cluster Analysis
Identify natural groupings of similar positions within the collected judgments. Characterize each cluster by its central position, shared reasoning patterns, and distinguishing features.
## Execution
Spawn a subagent that analyzes the judgments for similarity patterns, groups them into coherent clusters, and provides characterization of each cluster.
## Why Subagent
- Clustering requires holistic analysis of all judgments simultaneously
- Characterization is a bounded analytical task
- Output structure is standardized
## HARD-GATE
Output MUST contain: at least 2 clusters (if genuine disagreement exists), each with `cluster_id`, `position_summary`, `member_count`, and `characterization`. If all judgments agree, output 1 cluster with a note.
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