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technical-analysis

Analyze stock price data with RSI, MACD, Bollinger Bands, and ADX to determine market regime and tradeable levels.

18|3|Updated Jan 20, 2026
Search Tags:#stock analysis#technical analysis#trading strategies#market regime#indicator computations
One-click install
npx skills add https://github.com/mohitjandwani/analyst-kit --skill technical-analysis-mohitjandwani
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: technical-analysis
Source: https://github.com/mohitjandwani/analyst-kit/tree/main/plugins/analyst-kit/skills/technical-analysis
Command: npx skills add https://github.com/mohitjandwani/analyst-kit --skill technical-analysis-mohitjandwani

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the technical analysis of stock prices, identifying market regimes, confluence scores, and providing entry and exit levels for trading strategies.

Core Features & Use Cases

  • Market Regime Classification: Identifies whether the market is trending, ranging, or in a transitional state.
  • Confluence Score: Measures the agreement across three layers (regime, momentum, trigger) to determine a tradeable setup.
  • Entry and Exit Levels: Computes ATR-based stops, position size, trailing exits, and targets based on historical data and indicators.
  • Use Case: A trader can use this Skill to analyze a stock like AAPL, receiving a dashboard chart and a PDF report detailing potential entry and exit points.

Quick Start

Run the technical-analysis skill on the stock AAPL to generate a report.

Frequently Asked Questions about technical-analysis

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

FAQPage Schema
How do I conduct technical analysis on stocks with RSI and MACD indicators?▼

Technical analysis on stocks uses indicators like RSI, MACD, Bollinger Bands, and ADX to classify market regime, calculate confluence score, and determine tradeable entry and exit levels for daily or weekly timeframes.

How do I calculate entry and exit levels for trading strategies using ATR?▼

Calculating entry and exit levels for trading strategies uses ATR-based stops, position sizing, trailing exits, and targets derived from historical stock price data and momentum indicators to define actionable trade setups.

What is market regime classification and how does confluence score work?▼

Market regime classification identifies whether a stock is trending, ranging, or transitioning. Confluence score measures agreement across regime, momentum, and trigger layers to validate a tradeable setup for stock analysis.

Do I need Python and specific dependencies to compute stock indicator calculations?▼

Computing stock indicator calculations requires Python and the pandas, numpy, and matplotlib dependencies to process daily OHLCV data, calculate technical indicators, and generate dashboard charts.

Can I use this technical analysis approach for intraday trading timeframes?▼

This technical analysis approach is optimized for daily or weekly trading timeframes, using historical OHLCV data to identify market regimes and compute entry and exit levels, rather than intraday trading.

What is the best way to generate a technical analysis report for a stock like AAPL?▼

To generate a technical analysis report for a stock like AAPL, run the analysis on daily OHLCV data to produce a dashboard chart and a PDF report detailing market regime, confluence score, and potential entry and exit points.

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