trading-strategist

Name: trading-strategist
Author: kukapay

Data-driven cryptocurrency trading strategies combining Binance market data, technical indicators, and sentiment analysis. Integrates real-time and historical price/volume data from Binance with calculated TA indicators (SMA, RSI, MACD, Bollinger Bands, Stochastic) Aggregates market sentiment from crypto RSS feeds to inform buy/sell/hold signals and entry/exit recommendations Generates risk management guidance including stop-loss levels, position sizing (1-5% of capital), and volatility warnings Supports multiple timeframes and analysis depths, from quick ticker snapshots to extended 50-100 day historical analysis for swing trading

INSTALLATION

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

Run in your project or agent environment. Adjust flags if your CLI version differs.

SKILL.md

$2a

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

TA formulas: See references/ta_formulas.md

Sentiment interpretation: See references/sentiment_guide.md

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