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vector-cluster

Group related code files by analyzing a graph of their connections with ruvector. Review group assignments, community labels, and links between files to understand code organization and investigate files that stand apart.

中文简介正在准备中。当前显示英语简介。

原文查看原文说明

Cluster code by graph community detection via npx ruvector@0.3.3 hooks graph-cluster (spectral / Louvain)

查看安装方法

适用场景

  • Understanding groups of related code files
  • Reviewing connections between code groups
  • Investigating files that stand apart
  • Saving grouping results for later reference

包含的文件(1)

  • SKILL.md2.1 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

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@0.3.3 is available:
    npm ls ruvector 2>/dev/null | grep '0.3.3' || npm install ruvector@0.3.3
    
  2. Run clustering — in ruvector@0.3.3 the only working clustering is via hooks graph-cluster (spectral/Louvain over a code graph). The top-level cluster command is reserved for distributed cluster ops and is currently "Coming Soon" upstream.
    npx -y ruvector@0.3.3 hooks graph-cluster <files...>
    npx -y ruvector@0.3.3 hooks graph-mincut <files...>
    
  3. Review output — JSON with cluster assignments, community labels, and edges. If you see "graph.nodes is not iterable", run hooks init first to seed the graph state.
  4. Store results: mcp__plugin_ruflo-core_ruflo__memory_store({ key: "clusters-PROJECT-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 resolution
  • Outliers: novel or anomalous files worth investigating

Caveats

  • cluster --namespace ... --k N and cluster --density are not valid in ruvector@0.3.3 — those flags fall through to the distributed-cluster command, which only accepts --status, --join, --leave, --nodes, --leader, --info.
  • For namespaced k-means over arbitrary embeddings, run k-means in your own code against vectors stored in AgentDB.

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中文简介正在准备中。当前显示英语简介。

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中文简介正在准备中。当前显示英语简介。

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中文简介正在准备中。当前显示英语简介。

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中文简介正在准备中。当前显示英语简介。

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中文简介正在准备中。当前显示英语简介。

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中文简介正在准备中。当前显示英语简介。

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