Detect Fibonacci XABCD harmonic patterns and generate D-point trading signals from OHLCV data.
npx skills add https://github.com/wudye/traderAssistHK --skill harmonic-wudye
Please help me install this Agent Skill. Skill: harmonic Source: https://github.com/wudye/traderAssistHK/tree/main/backend/src/skills/harmonic Command: npx skills add https://github.com/wudye/traderAssistHK --skill harmonic-wudye
This Skill helps you identify XABCD harmonic patterns (Gartley, Bat, Butterfly, Crab) and translate their D-point convergence into actionable long/short/flat trading signals.
Use case example: Analyze daily OHLCV for BTC/ETH to mark historical dates where harmonic patterns complete at PRZ, producing a time-aligned signal series (1 for long, -1 for short, 0 to stand aside) for backtesting.
Use the harmonic signal engine to generate PRZ-based buy/sell signals from a map of symbols to OHLCV DataFrames indexed by datetime.
High-intent search queries and answers about installing and using this skill.
Harmonic patterns are identified by validating Fibonacci ratio constraints on XABCD swing points extracted from OHLCV price series. This Skill classifies Gartley, Bat, Butterfly, and Crab formations and outputs a time-aligned signal series for backtesting.
Trading signals are generated at the D-point where Potential Reversal Zone (PRZ) convergence is expected. This Skill processes OHLCV inputs to emit per-timestamp signals using 1 for long, -1 for short, and 0 for stand aside.
Yes, this Skill applies pyharmonics to detect harmonic patterns for backtesting across instruments like crypto pairs or stocks. It processes historical OHLCV charts and includes a built-in deterministic fallback detector if pyharmonics is unavailable.
Scanning historical charts for Fibonacci retracement patterns is done by processing OHLCV DataFrames indexed by datetime. This Skill validates Fibonacci ratio tolerances on swing points to classify XABCD harmonic patterns and output actionable signals.
Yes, pandas and numpy are required dependencies for handling OHLCV DataFrames and numerical operations during harmonic pattern detection. The Skill also uses requests for data fetching and pyharmonics, with a deterministic fallback if the latter is missing.
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