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clustercluster 分析

Agent Skill

cluster 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

7,295

周安装

298

GitHub Stars

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下载量

2,336
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:cluster(cluster 分析)
来源仓库:https://github.com/ckchzh/cluster
安装命令:
openclaw skills install cluster
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install cluster

简介

使用 k 均值和分层算法执行数据聚类分析。当您需要对数据集进行分组、分类或分段时使用。

SKILL.md

name
cluster
version
1.0.0
description
Perform data clustering analysis using k-means and hierarchical algorithms. Use when you need to group, classify, or segment datasets.
author
BytesAgain
homepage
https://bytesagain.com
source
https://github.com/bytesagain/ai-skills
tags
[data, clustering, analysis, machine-learning, k-means, segmentation]

Cluster — Data Clustering Analysis Tool

Cluster is a command-line data clustering analysis tool that supports k-means and hierarchical clustering algorithms. It reads numerical data from CSV/JSONL sources, performs clustering, evaluates cluster quality, and exports results.

Data is stored in ~/.cluster/data.jsonl as JSONL records. Each record represents a clustering run with its parameters, assignments, centroids, and evaluation metrics.

Prerequisites

  • Python 3.8+ with standard library (no external packages required for basic operations)
  • bash shell

Commands

run

Run a clustering algorithm on input data.

Environment Variables:

  • INPUT (required) — Path to input CSV/JSONL file with numerical data
  • K — Number of clusters (default: 3)
  • ALGORITHM — Algorithm to use: kmeans or hierarchical (default: kmeans)
  • MAX_ITER — Maximum iterations for k-means (default: 100)
  • SEED — Random seed for reproducibility

Example:

INPUT=/path/to/data.csv K=5 ALGORITHM=kmeans bash scripts/script.sh run

assign

Assign new data points to existing clusters from a previous run.

Environment Variables:

  • RUN_ID (required) — ID of the clustering run to use
  • INPUT (required) — Path to new data points (CSV/JSONL)

Example:

RUN_ID=abc123 INPUT=/path/to/new_data.csv bash scripts/script.sh assign

centroids

Display or export centroid coordinates for a clustering run.

Environment Variables:

  • RUN_ID (required) — ID of the clustering run
  • FORMAT — Output format: table, json, csv (default: table)

evaluate

Evaluate clustering quality with silhouette score, inertia, and Davies-Bouldin index.

Environment Variables:

  • RUN_ID (required) — ID of the clustering run to evaluate

visualize

Generate a text-based or ASCII visualization of cluster assignments.

Environment Variables:

  • RUN_ID (required) — ID of the clustering run
  • DIMS — Dimensions to plot, comma-separated (default: first two)

export

Export clustering results to a file.

Environment Variables:

  • RUN_ID (required) — ID of the run to export
  • OUTPUT — Output file path (default: stdout)
  • FORMAT — Export format: json, csv, jsonl (default: json)

import

Import a previously exported clustering run.

Environment Variables:

  • INPUT (required) — Path to the file to import

config

View or update configuration settings.

Environment Variables:

  • KEY — Configuration key to set
  • VALUE — Configuration value

list

List all stored clustering runs with summary info.

Environment Variables:

  • LIMIT — Maximum runs to display (default: 20)
  • SORT — Sort field: date, k, score (default: date)

stats

Show aggregate statistics across all clustering runs.

help

Display usage information and available commands.

version

Display the current version of the cluster tool.

Data Storage

All clustering runs are stored in ~/.cluster/data.jsonl. Each line is a JSON object with fields:

  • id — Unique run identifier
  • timestamp — ISO 8601 creation time
  • algorithm — Algorithm used
  • k — Number of clusters
  • centroids — List of centroid coordinates
  • assignments — Mapping of data point indices to cluster IDs
  • metrics — Evaluation metrics (silhouette, inertia, etc.)
  • input_file — Source data file path
  • num_points — Number of data points clustered

Configuration

Config is stored in ~/.cluster/config.json. Available keys:

  • default_k — Default number of clusters (default: 3)
  • default_algorithm — Default algorithm (default: kmeans)
  • max_iterations — Default max iterations (default: 100)
  • random_seed — Default random seed (default: 42)

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适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

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按下载量换算1,749

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通过

Static analysis

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敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

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来源信息

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