harmonic

Detect XABCD harmonic trading patterns from OHLCV market data.

Updated Jun 30, 2026
One-click install
npx skills add https://github.com/0xZKnw/vibe-trading-tap --skill harmonic-0xzknw
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: harmonic
Source: https://github.com/0xZKnw/vibe-trading-tap/tree/main/agent/src/skills/harmonic
Command: npx skills add https://github.com/0xZKnw/vibe-trading-tap --skill harmonic-0xzknw

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This skill addresses the difficulty of manually identifying complex XABCD harmonic patterns in volatile financial markets, which often leads to missed opportunities or human error in calculating precise Fibonacci ratios.

Core Features & Use Cases

  • Pattern Recognition: Automatically detects Gartley, Bat, Butterfly, and Crab patterns using Fibonacci geometry.
  • PRZ Identification: Pinpoints the Potential Reversal Zone (PRZ) where price reversal probability is statistically higher.
  • Use Case: A trader can use this to scan daily crypto or stock price data to find high-probability entry points based on historical geometric structures.

Quick Start

Use the harmonic skill to analyze the latest market data for BTC-USDT and identify any active reversal patterns.

Frequently Asked Questions about harmonic

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

FAQPage Schema
How do I identify XABCD harmonic patterns in OHLCV market data?

To identify XABCD harmonic patterns in OHLCV market data, you calculate Fibonacci ratio relationships between price swings to validate geometric structures. This detects five-point patterns and pinpoints potential reversal zones for automated signal generation.

What harmonic trading patterns can I detect using Fibonacci geometry?

Using Fibonacci geometry, you can detect harmonic trading patterns like Gartley, Bat, Butterfly, and Crab. These are validated by calculating precise Fibonacci ratios between price swings to find high-probability reversal zones.

Can I use pandas and numpy to scan crypto price data for harmonic patterns?

Yes, you can use pandas and numpy to scan daily crypto or stock price data for harmonic patterns. By processing OHLCV market data, the numerical analysis validates geometric structures against predefined pattern ratios to find active reversal patterns.

What is a Potential Reversal Zone in harmonic pattern recognition?

A Potential Reversal Zone (PRZ) in harmonic pattern recognition is a calculated price area where reversal probability is statistically higher. It is identified by validating Fibonacci ratio relationships across five-point XABCD price swings.

Does automated harmonic pattern detection require manual Fibonacci calculations?

Automated harmonic pattern detection eliminates manual Fibonacci calculations, addressing the human error inherent in identifying complex XABCD patterns in volatile financial markets. It automatically validates geometric structures against predefined pattern ratios using numerical analysis.

What are the limitations of using harmonic patterns for trading signals?

The limitation of using harmonic patterns for trading signals is that pattern detection relies on historical geometric structures, which do not guarantee future price reversals. Validating XABCD patterns in volatile financial markets requires precise numerical analysis of price action to avoid missed opportunities.