Detect Chanlun price patterns and generate buy/sell signals from OHLCV data.
npx skills add https://github.com/GGwujun/SigmX --skill chanlun-ggwujun
Please help me install this Agent Skill. Skill: chanlun Source: https://github.com/GGwujun/SigmX/tree/main/agent/src/skills/chanlun Command: npx skills add https://github.com/GGwujun/SigmX --skill chanlun-ggwujun
Automates Chanlun-based price-pattern recognition and buy/sell signal generation from OHLCV data, enabling traders to quickly identify trend turns and actionable signals.
Feed OHLCV data into the SignalEngine to generate real-time Chanlun buy/sell signals.
High-intent search queries and answers about installing and using this skill.
To generate Chanlun buy/sell signals from OHLCV data, feed your multi-period OHLCV records into the provided SignalEngine. The engine processes the data to detect price patterns and outputs directional signals like first-buy or third-sell.
Chanlun price patterns are structural trend formations consisting of FX, BI, and ZS segments detected from OHLCV data. The signal engine automates this recognition by analyzing K-line structures across multiple timeframes to identify trend turns.
Yes, you can use the czsc library for multi-timeframe trend analysis. The Skill requires Python 3.x and leverages czsc to process OHLCV data across different periods, enabling cross-timeframe Chanlun pattern detection and signal generation.
Chanlun pattern recognition works for any market with available OHLCV data, including crypto and A-share instruments. You can apply it to build real-time signal feeds or backtest trend-based trading decisions across these assets.
The Chanlun signal engine generates specific buy/sell signals including first-buy, first-sell, third-buy, and third-sell. These signals are outputted with contextual hints to help traders identify actionable trend reversals.
Yes, you need Python 3.x to run Chanlun pattern detection. The Skill's internal signal engine and its dependency on the czsc library require a Python 3.x environment to process OHLCV data and output trading signals.
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