yogsoth-ai 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.
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. |