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technical-indicators

Compute TA-Lib technical indicators and signals from OpenAlgo market data.

2|5|Updated Jan 4, 2026
Search Tags:#data-analysis#backtesting#trading#technical-indicators#ta-lib#openalgo
One-click install
npx skills add https://github.com/marketcalls/openalgo-claude-plugin --skill technical-indicators-marketcalls
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: technical-indicators
Source: https://github.com/marketcalls/openalgo-claude-plugin/tree/main/plugins/openalgo-python/skills/technical-indicators
Command: npx skills add https://github.com/marketcalls/openalgo-claude-plugin --skill technical-indicators-marketcalls

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires ta-lib, numpy, pandas, openalgo, and includes scripts (resource) components.

What problem does it solve?

Compute and apply TA-Lib based technical indicators (SMA, EMA, RSI, MACD, Bollinger Bands, Stochastic, ATR, and candlestick pattern recognitions) on OpenAlgo market data to support strategy development, backtesting, and live decision making.

Core Features & Use Cases

  • Indicator suite: Implements moving averages, momentum, volatility, volume, and candlestick-pattern features using TA-Lib on OpenAlgo data.
  • Signal generation: Produces simple signals and helper metrics (crossovers, overbought/oversold, trend strength) for building automated strategies.
  • Use Case: A quant trader can compute a combined RSI/MACD or BB squeeze strategy on NSE or NFO data and feed results into a backtesting workflow.

Quick Start

Run the indicators tool against a symbol and a time frame to generate TA-Lib based indicators and signals.

Frequently Asked Questions about technical-indicators

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I compute TA-Lib technical indicators for trading using OpenAlgo market data?▼

You compute TA-Lib technical indicators by running the scripts tool against an OpenAlgo symbol and time frame, which calculates momentum, volatility, and candlestick pattern signals for backtesting workflows.

What technical indicators can I generate from OpenAlgo price series for backtesting?▼

You can generate technical indicators including SMA, EMA, RSI, MACD, Bollinger Bands, Stochastic, ATR, and candlestick pattern recognitions from OpenAlgo price series to produce crossover, overbought, and trend strength signals for backtesting.

Do I need a system TA-Lib library and OpenAlgo API key to run technical indicator scripts?▼

Yes, running technical indicator scripts requires the system TA-Lib library, numpy, and pandas, plus access to the OpenAlgo API configured through the OPENALGO_API_KEY and OPENALGO_HOST environment variables to retrieve market data.

Can I apply TA-Lib indicators to NSE or NFO exchange data for automated strategy development?▼

Yes, you can apply TA-Lib indicators to price series across supported exchanges like NSE or NFO to compute combined RSI/MACD or Bollinger Band squeeze strategies, producing helper metrics and signals for automated strategy development and backtesting.

What's the best way to generate candlestick pattern signals and momentum indicators with TA-Lib and pandas?▼

The best way to generate candlestick pattern signals and momentum indicators is using this Skill's TA-Lib implementation with pandas and numpy on OpenAlgo market data, which natively outputs trend strength, overbought/oversold metrics, and pattern recognitions.

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