harmonic

Name: harmonic
Availability: InStock
Author: OpenSucker

Detect Fibonacci-based harmonic price patterns in market data.

15|2|Updated May 1, 2026

Search Tags:#market analysis #pattern recognition #technical analysis #trading signals #fibonacci #harmonic patterns

Ready to run

npx skills add https://github.com/OpenSucker/OpenSucker --skill harmonic-opensucker

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: harmonic
Source: https://github.com/OpenSucker/OpenSucker/tree/main/skills/vibe_skills/harmonic
Command: npx skills add https://github.com/OpenSucker/OpenSucker --skill harmonic-opensucker

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pyharmonics, pandas, numpy, requests, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill enables traders to identify complex harmonic patterns, such as Gartley, Bat, Butterfly, and Crab, based on Fibonacci geometry, facilitating more accurate reversal signals.

Core Features & Use Cases

Pattern Recognition: Detects five-point harmonic structures using Fibonacci ratios on price data.
Signal Generation: Identifies potential reversal zones (PRZ) and generates trading signals accordingly.
Use Case: A trader analyzes historical price data to find Gartley or Bat patterns, then makes informed entry and exit decisions.
Quick Start: Use the harmonic pattern detection engine on your price data to identify potential reversal points.

Quick Start

Apply the harmonic pattern engine to your historical price series to identify actionable trading signals and reversal zones.

Frequently Asked Questions about harmonic

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

FAQPage Schema

How do I detect harmonic patterns like Gartley or Bat in my price data?▼

Harmonic patterns like Gartley and Bat are identified by applying a Fibonacci-ratio detection engine to your historical price data. This process recognizes five-point geometric structures to help locate potential reversal zones.

What are Fibonacci-based harmonic patterns in technical analysis?▼

Fibonacci-based harmonic patterns are five-point geometric price structures, such as the Crab or Butterfly, that use specific Fibonacci ratios. They identify potential reversal zones to generate actionable technical trading signals.

Do I need Python packages like pandas and numpy to scan for harmonic trading signals?▼

Yes, scanning for harmonic trading signals requires Python packages like pandas, numpy, requests, and pyharmonics. These dependencies handle the data manipulation and mathematical calculations required to detect the patterns accurately.

Can I use harmonic pattern recognition to find potential reversal zones for my trading strategy?▼

Yes, harmonic pattern recognition finds potential reversal zones (PRZ) by analyzing historical market data within specific price and Fibonacci ratio parameters. It successfully generates actionable entry and exit signals for trading strategies.

Does automated harmonic pattern detection work with standard market data?▼

Automated harmonic pattern detection works directly with standard market data formatted as a historical price series. The engine processes this information to evaluate Fibonacci ratios and map five-point geometric structures automatically.

What is the best way to identify Butterfly and Crab patterns automatically?▼

The best way to identify Butterfly and Crab patterns automatically is to run a specialized pattern recognition engine on your historical price series. It calculates the required Fibonacci geometry to confirm these specific harmonic structures.