vector-cluster

Vector Cluster

Cluster vectors in a namespace by semantic similarity using ruvector.

When to use

Use this skill when you have a collection of embeddings and want to discover natural groupings. Clustering reveals themes, identifies outliers, and helps organize large vector collections.

Steps

1. Ensure ruvector is available:

   npm ls ruvector 2>/dev/null || npm install ruvector
   

2. Run clustering:
   • With known cluster count: npx ruvector cluster --namespace NAMESPACE --k N
   • With auto-detection: npx ruvector cluster --namespace NAMESPACE --density
3. Review output -- ruvector reports: cluster ID, label, member count, cohesion score, and outliers (for density mode)
4. Store results: mcp__claude-flow__memory_store({ key: "clusters-NAMESPACE-TIMESTAMP", value: "CLUSTER_ASSIGNMENTS", namespace: "vector-clusters" })

Interpreting results

• High cohesion (>0.85): tight, well-defined cluster
• Medium cohesion (0.6-0.85): related but diverse content
• Low cohesion (<0.6): loose grouping, try higher k
• Outliers: novel or anomalous entries worth investigating

Graph-based clustering (ruvector v2.1+)

ruvector supports Louvain community detection and spectral clustering for graph-structured data:

npx ruvector hooks graph-cluster --namespace NAMESPACE
npx ruvector hooks graph-mincut --namespace NAMESPACE