ichimoku

Detect Ichimoku TK crossovers filtered by cloud position and direction from OHLC data.

Updated Apr 9, 2026
One-click install
npx skills add https://github.com/JacobHsu/vibe-trading-agent --skill ichimoku-jacobhsu
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ichimoku
Source: https://github.com/JacobHsu/vibe-trading-agent/tree/main/agent/src/skills/ichimoku
Command: npx skills add https://github.com/JacobHsu/vibe-trading-agent --skill ichimoku-jacobhsu

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill codifies the Ichimoku Kinko Hyo five-line framework so you no longer have to eyeball crossovers, cloud orientation, and confirmation manually, enabling consistent signal generation with pandas.

Core Features & Use Cases

  • Five-line computation: Calculates Tenkan-sen, Kijun-sen, Senkou Span A/B, and the Lagging Span with the required 78-candle warm-up, providing full context for trend evaluation.
  • Triple-filtered signals: Emits long or short signals only when TK crossovers align with price being above/below the cloud and with corresponding bullish or bearish cloud direction, delivering deterministic 1/0/-1 outputs.
  • Reference documentation: Includes detailed notes explaining each line and the signal logic to help traders adjust periods and verify the engine’s reasoning in strategy development.

Quick Start

Use the ichimoku skill to analyze a symbol's daily candles and report whether a strong TK crossover currently aligns with cloud confirmation.

Frequently Asked Questions about ichimoku

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

FAQPage Schema
How do I generate Ichimoku trading signals from OHLC data using pandas?

Ichimoku Kinko Hyo signals trigger when a TK crossover aligns with price position above or below the cloud and the corresponding cloud direction. This triple-filter mechanism ensures trend confirmation before emitting deterministic long or short outputs.

Can I use this Ichimoku strategy for intraday crypto feeds?

Yes, you can apply this Ichimoku strategy to intraday crypto feeds. It processes daily or intraday OHLC data using a dependency-free pandas implementation, requiring a 78-candle warm-up to calculate Tenkan-sen, Kijun-sen, and Senkou Spans for accurate trend evaluation.

What's the best way to backtest Ichimoku crossover strategies deterministically?

The best way to backtest Ichimoku crossover strategies deterministically is using a pandas implementation that manages the 78-candle warm-up and applies strict triple-filtered signal conventions, ensuring consistent 1/0/-1 outputs for trend entries and exits without visual charting ambiguity.

Why does my Ichimoku cloud calculation require a 78-candle warm-up?

An Ichimoku cloud calculation requires a 78-candle warm-up because computing the full five-line framework, especially the Lagging Span and Senkou Span B shifted forward, needs sufficient historical data to populate accurately before generating valid trend-confirmed crossover signals.

Are there limitations to using pandas for technical analysis signal generation on equity feeds?

A limitation of using pandas for technical analysis signal generation on equity feeds is that it requires strictly structured OHLC data and a fixed 78-candle warm-up period, meaning insufficient historical data will prevent the indicator from producing valid trend-confirmed outputs.