Provides trading strategies for cryptocurrencies based on Binance market data, calculated technical analysis indicators, and aggregated market sentiment from crypto RSS news feeds. Use when users ask for trading advice, strategy recommendations, or analysis combining price data, TA, and sentiment fo

Trading Strategies Skill This skill generates data driven trading strategies for cryptocurrencies by integrating multiple data sources and analytical tools. Core Components 1. Binance Market Data : Real time price, volume, and historical klines from Binance API 2. Technical Analysis (TA) : Calculated indicators including SMA, RSI, MACD, Bollinger Bands, Stochastic, and more 3. Market Sentiment : Aggregated sentiment scores from popular crypto RSS feeds Workflow Step 1: Data Collection Fetch current ticker data from Binance API ( /api/v3/ticker/price and /api/v3/ticker/24hr ) Retrieve historical klines ( /api/v3/klines with 30 100 days of data) Aggregate sentiment using the market sentiment skill Step 2: TA Calculation Use the scripts/calculate ta.py script to compute indicators from historical data. Step 3: Strategy Generation Combine TA signals, price action, and sentiment score to recommend: Buy/Sell/Hold signals Entry/exit points Risk management (stop loss, position sizing) Timeframes (swing, day trading) Usage Examples Basic Strategy Request → Fetch ETH data, calculate TA, get sentiment, output strategy. Advanced Analysis → Use longer history, focus on swing signals. Risk Management Always include stop loss recommendations Suggest position sizes (1 5% of capital) Warn about volatility and leverage risks Note: Not financial advice References TA formulas: See [references/ta formulas.md](references/ta formulas.md) Sentiment interpretation: See [references/sentiment guide.md](references/sentiment guide.md) Scripts scripts/calculate ta.py : Python script for TA indicator calculations scripts/fetch binance.py : Helper for Binance API calls</content <parameter name="filePath" ./skills/trading strategies/SKILL.md

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