Technical Analysis

Computes standard technical indicators using pandas-ta and yfinance. You get RSI, MACD, Bollinger Bands, moving averages, ATR, and ADX with built-in signal interpretation like overbought/oversold thresholds and golden crosses. Handles multi-symbol analysis in one call and includes a separate correlation script for portfolio diversification checks. The risk metrics (Sharpe ratio, annualized volatility) and earnings data integration are nice touches. Output is JSON with clear signal summaries, so you don't have to remember what RSI 75 means. Works well for quick sentiment checks on tickers without opening TradingView, though you're still doing your own research on top of these numbers.

skills.sh installs: 598
GitHub stars: 406
last updated: Aug 21, 2026

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Install

$ npx -y skills add staskh/trading_skills --skill technical-analysis --agent claude-code

Installs into .claude/skills of the current project.

Files

Technical Analysis

Compute technical indicators using pandas-ta. Supports multi-symbol analysis and earnings data.

Instructions

Note: If uv is not installed or pyproject.toml is not found, replace uv run python with python in all commands below.

uv run python scripts/technicals.py SYMBOL [--period PERIOD] [--indicators INDICATORS] [--earnings]

Arguments

SYMBOL - Ticker symbol or comma-separated list (e.g., AAPL or AAPL,MSFT,GOOGL)
--period - Historical period: 1mo, 3mo, 6mo, 1y (default: 3mo)
--indicators - Comma-separated list: rsi,macd,bb,sma,ema,atr,adx (default: all)
--earnings - Include earnings data (upcoming date + history)