theme-detector

Name: theme-detector
Availability: InStock
Author: ihsandanish25

Detect and analyze trending market themes across sectors with confidence scores.

2|Updated Jun 14, 2026

Search Tags:#financial analysis #investment analysis #sector analysis #market themes #lifecycle maturity

Ready to run

npx skills add https://github.com/IhsanDanish25/claude-trading-skills --skill theme-detector-ihsandanish25

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: theme-detector
Source: https://github.com/IhsanDanish25/claude-trading-skills/tree/main/skills/theme-detector
Command: npx skills add https://github.com/IhsanDanish25/claude-trading-skills --skill theme-detector-ihsandanish25

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, beautifulsoup4, lxml, pandas, numpy, yfinance, finvizfinance, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill helps traders detect and analyze trending market themes across sectors, assess their lifecycle maturity, and provide confidence scores for investment insights.

Core Features & Use Cases

Cross-Sector Theme Detection: Analyze momentum, volume, and breadth signals across multiple sectors.
Bullish and Bearish Themes: Identify themes with upward or downward momentum.
Lifecycle Maturity Assessment: Classify themes as Emerging, Accelerating, Trending, Mature, or Exhausting.
Confidence Scores: Combine quantitative data with narrative analysis to provide reliability.
Use Case: A trader looking to understand the current market themes and identify potential investment opportunities can use this Skill to assess themes and their potential for future performance.

Quick Start

Use the theme-detector skill to detect trending market themes.

Frequently Asked Questions about theme-detector

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

FAQPage Schema

How do I detect trending market themes across multiple sectors?▼

To detect trending market themes across sectors, you can analyze momentum, volume, and breadth signals. This approach classifies bullish and bearish themes while assessing their lifecycle maturity to provide confidence scores for investment insights.

What is lifecycle maturity assessment in investment analysis?▼

Lifecycle maturity assessment in investment analysis classifies market themes into Emerging, Accelerating, Trending, Mature, or Exhausting stages. It helps traders understand the current phase of a theme to evaluate its potential for future performance.

How do I get sector analysis confidence scores using Python and yfinance?▼

You can generate sector analysis confidence scores by combining quantitative data from sources like yfinance with narrative analysis. The process requires Python libraries including pandas, numpy, and beautifulsoup4 to process momentum and breadth signals.

Do I need FINVIZ Elite or FMP API keys for market theme analysis?▼

You do not need FINVIZ Elite or FMP API keys for market theme analysis. The Skill supports public scraping mode by default, but optional API keys for FINVIZ Elite or FMP API provide enhanced data for more accurate bullish and bearish theme detection.

Can I use beautifulsoup4 and lxml for cross-sector theme detection?▼

Yes, you can use beautifulsoup4 and lxml for cross-sector theme detection. They are required dependencies for parsing market data when analyzing momentum, volume, and breadth signals without utilizing optional FINVIZ Elite API keys.

What are the limitations of using public scraping mode for financial analysis?▼

Public scraping mode for financial analysis may provide limited or delayed data compared to using FINVIZ Elite or FMP API keys. It relies on beautifulsoup4 and lxml to extract sector momentum and breadth signals, which can affect confidence score accuracy.