candlestick

Identify candlestick patterns and generate trading signals from price data.

Updated May 25, 2026

Search Tags:#pandas #financial analysis #technical indicators #trading signals #candlestick patterns

Ready to run

npx skills add https://github.com/NigarumOvum/AutoTrading --skill candlestick-nigarumovum

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: candlestick
Source: https://github.com/NigarumOvum/AutoTrading/tree/main/Vibe-Trading/agent/src/skills/candlestick
Command: npx skills add https://github.com/NigarumOvum/AutoTrading --skill candlestick-nigarumovum

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps users identify and interpret 15 classic candlestick patterns to inform trading decisions.

Core Features & Use Cases

Candlestick Pattern Recognition: Automatically detects patterns such as hammers, engulfing, and doji from financial price data.
Trading Signals: Scores each pattern for bullishness or bearishness and generates signals to go long, short, or stand aside.
Use Case: Ideal for technical traders looking to add pattern-based insights into their analysis, aiding in decision-making for stocks, forex, or other assets.

Quick Start

Activate the candlestick skill to identify trading signals for the last 5 days of price data from 'market_prices.csv'.

Frequently Asked Questions about candlestick

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

FAQPage Schema

How do I identify candlestick patterns in pandas?▼

This Skill generates trading signals by scoring each detected candlestick pattern for bullishness or bearishness, translating these scores into actionable signals to go long, short, or stand aside.

Can I use pandas to generate trading signals from price data?▼

Yes, you can use pandas to generate trading signals from price data by applying vectorized statistical calculations that score candlestick patterns for bullish or bearish sentiment and output actionable trading decisions.

Do I need numpy to detect candlestick patterns?▼

Yes, you need both pandas and numpy installed, as numpy handles the underlying statistical calculations required to process the time-series financial data and detect the patterns.

What is the best way to analyze candlestick patterns for multiple assets?▼

The best way to analyze multiple assets is using a pandas vectorized implementation, which processes time-series financial data efficiently to identify market trends and sentiment across various stocks or forex pairs.

Does this candlestick pattern detection work with forex data?▼

Yes, this candlestick pattern detection works with forex data, as it processes standard financial price time-series data to aid technical analysis and decision-making across various asset classes.