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anomalous-attractor-detector

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Detects UAP-like phase transitions and strange attractors in time-series data.

Data & Analytics#anomaly detection#phase transition#time-series analysis#UAP#strange attractor
AuthorEvezArt
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill identifies unusual patterns and phase transitions in time-series data, such as those indicative of Unidentified Aerial Phenomena (UAP) events.

Core Features & Use Cases

  • Anomaly Detection: Flags UAP-like phase transitions in scalar time-series data.
  • Strange Attractor Detection: Identifies chaotic attractors in data.
  • Use Case: Use this Skill to analyze atmospheric, behavioral, or financial data for signs of unusual activity that may be indicative of UAP events.

Quick Start

Run the anomalous-attractor-detector skill on the time-series data file 'uap_data.csv'.

Dependency Matrix

Required Modules

None required

Components

scripts

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: anomalous-attractor-detector
Download link: https://github.com/EvezArt/evez-skills/archive/main.zip#anomalous-attractor-detector

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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