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trading-strategist

trading-strategist

github.com/kukapayOther371.0k installsUpdated 25w ago
Repository

About trading-strategist

trading-strategist is a skill for generating cryptocurrency trading strategies from Binance market data, technical indicators, and aggregated sentiment. It combines these inputs into signals, entry and exit points, and risk guidance.

Key features

  1. 01Fetches current and historical Binance data
  2. 02Calculates SMA, RSI, MACD, and other indicators
  3. 03Incorporates sentiment from crypto RSS feeds
  4. 04Generates buy, sell, or hold signals
  5. 05Suggests stops and position sizing

Use cases

  1. 01Analyze ETH using current market data and sentiment
  2. 02Assess BTC over a specified historical period
  3. 03Generate swing or day-trading recommendations

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/kukapay/crypto-skills --skill trading-strategist

After installing, type/trading-strategistin Claude Code to confirm it loaded.

Bundled filesscripts/calculate_ta.py

Details

From the project README

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
For ETH, generate a trading strategy based on current market data.

→ Fetch ETH data, calculate TA, get sentiment, output strategy.

Advanced Analysis
Analyze BTC with 50-day history, include sentiment, recommend swing trade.

→ 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

Scripts

  • scripts/calculate_ta.py: Python script for TA indicator calculations
  • scripts/fetch_binance.py: Helper for Binance API calls ./skills/trading-strategies/SKILL.md

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