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technical-analysis-engine

Compute technical indicators and market-structure metrics from OHLCV data.

5|Updated Apr 8, 2026
Search Tags:#python#indicators#technical-analysis#screener#forex#market-structure
One-click install
npx skills add https://github.com/JansenAnalytics/claudex --skill technical-analysis-engine
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: technical-analysis-engine
Source: https://github.com/JansenAnalytics/claudex/tree/main/skills/technical-analysis-engine
Command: npx skills add https://github.com/JansenAnalytics/claudex --skill technical-analysis-engine

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, pandas_ta, numpy, and includes scripts (resource) components.

What problem does it solve?

Quickly assesses financial instruments by computing a full suite of technical indicators and screening for actionable trade setups, reducing manual TA workload for traders.

Core Features & Use Cases

  • Computes RSI, MACD, EMA, Bollinger Bands, ATR, Stochastic for rapid technical analysis.
  • Scans forex and other instruments for momentum, reversal, squeeze, and trend-pullback setups.
  • Analyzes market structure including BOS/CHoCH, support/resistance zones, order blocks, fair value gaps, and regime classification to support swing-trade decisions.
  • Supports multi-timeframe checks and ticker-level analysis to validate signals.

Quick Start

Analyze EURUSD with default daily data to generate a full technical analysis report.

Frequently Asked Questions about technical-analysis-engine

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

FAQPage Schema
How do I automate technical analysis screening for forex instruments?▼

Automate technical analysis screening by feeding OHLCV market data into a Python script that uses pandas-ta to compute indicators and scan for momentum, reversal, squeeze, and trend-pullback setups across forex tickers.

Can I detect market structure shifts like BOS and CHoCH using Python?▼

Yes, market structure shifts like BOS and CHoCH are detected by analyzing OHLCV data to classify regimes, map support/resistance zones, and identify order blocks and fair value gaps for swing trading.

Does this technical analysis engine require pandas and numpy to calculate RSI and MACD?▼

Yes, the technical analysis engine requires pandas, numpy, and pandas-ta as dependencies to calculate technical indicators like RSI, MACD, EMA, Bollinger Bands, ATR, and Stochastic from OHLCV data.

What is the best way to perform multi-timeframe checks for trading signals?▼

Perform multi-timeframe checks by running the technical analysis engine across different timeframes of OHLCV data to validate ticker-level signals and generate structured summaries of regime, structure trend, and zones.

How do I compute a full suite of technical indicators for daily market analysis?▼

Compute a full suite of technical indicators for daily market analysis by passing daily OHLCV data through the pandas-ta powered script, which outputs structured metrics including regime, structure_trend, and signal summaries.

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