gang-cluster-analysis

Identify potential gangs or clusters in phone networks using shared devices and common contacts.

Updated Jun 2, 2026

Search Tags:#cluster analysis #phone network #shared device #gang analysis #common contact

Ready to run

npx skills add https://github.com/bettercallfan/deerflow --skill gang-cluster-analysis

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: gang-cluster-analysis
Source: https://github.com/bettercallfan/deerflow/tree/main/skills/custom/phone-network-analysis/gang-cluster-analysis
Command: npx skills add https://github.com/bettercallfan/deerflow --skill gang-cluster-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill identifies potential gangs/clusters within a phone network based on shared devices, common contacts, and other relationships.

Core Features & Use Cases

Gang/Cluster Identification: Detects suspicious groups of phone numbers or individuals within a network.
Shared Device Analysis: Identifies devices shared among members of a potential gang/cluster.
Common Contact Analysis: Analyzes common contacts among members of a potential gang/cluster.
Use Case: For instance, analyze a set of phone numbers to identify if they belong to a gang/cluster based on shared devices and common contacts.

Quick Start

Run the gang-cluster-analysis skill with the provided sample phone numbers, e.g., gang-cluster-analysis --phone-id-file /path/to/sample_group_ids.txt.

Frequently Asked Questions about gang-cluster-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I identify gangs or clusters in a phone network?▼

Gang cluster analysis in a phone network identifies suspicious groups by analyzing shared devices and common contacts among phone numbers. It detects clusters of individuals connected through overlapping device usage and mutual contacts.

What is shared device analysis for fraud detection in phone networks?▼

Shared device analysis for fraud detection identifies when multiple phone numbers or individuals use the same physical devices. It flags these overlapping device patterns to detect coordinated suspicious activity within a network.

How do I run cluster analysis on a list of phone numbers?▼

To run cluster analysis, execute the skill with a file containing target phone numbers, such as passing a text file path to the command line interface. The tool processes the identifiers to detect interconnected groups.

Do I need Python libraries for graph analysis to detect common contacts?▼

Yes, you need access to phone network data and relevant Python libraries for graph analysis and data processing to detect common contacts. These libraries enable the network relationship mapping required for cluster identification.

Can I use phone network cluster analysis for threat intelligence?▼

Yes, phone network cluster analysis applies to threat intelligence scenarios by identifying potential gangs and suspicious groups. It maps shared relationships and common contacts to reveal coordinated threat networks.

When should I not use gang analysis for social network analysis?▼

Gang analysis for social network analysis is not suitable when you lack direct access to phone network data or sufficient shared device and common contact records. The cluster detection relies on these specific relationship inputs.