How do I install trading-strategist?

Run `npx skills add https://github.com/kukapay/crypto-skills --skill trading-strategist` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does trading-strategist support?

trading-strategist works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is trading-strategist free to use?

Yes. trading-strategist is free to install and use. It is available from the open Skills registry published by kukapay.

Productivity

trading-strategist▌

Name: trading-strategist
Availability: InStock
Author: kukapay

kukapay/crypto-skills · updated Apr 8, 2026

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

summary

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 volatil

skill.md

Trading Strategies Skill

This skill generates data-driven trading strategies for cryptocurrencies by integrating multiple data sources and analytical tools.

Core Components

Binance Market Data: Real-time price, volume, and historical klines from Binance API
Technical Analysis (TA): Calculated indicators including SMA, RSI, MACD, Bollinger Bands, Stochastic, and more
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

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