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theme-detector

Aggregate FINVIZ sector and industry data into ranked market theme heat maps.

Updated Aug 23, 2026
Search Tags:#momentum#theme#lifecycle#uptrend#finviz#thematic-investing#market-themes
One-click install
npx skills add https://github.com/PNWSkyHippy/Trading_Bot_V2 --skill theme-detector-pnwskyhippy
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: theme-detector
Source: https://github.com/PNWSkyHippy/Trading_Bot_V2/tree/main/claud-skills/skills/theme-detector
Command: npx skills add https://github.com/PNWSkyHippy/Trading_Bot_V2 --skill theme-detector-pnwskyhippy

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Detects and ranks current market themes by cross-sector momentum to help users understand broad market narratives and identify where sectors, themes, and rotations are shifting.

Core Features & Use Cases

  • Cross-sector theme detection using FINVIZ sector data and industry performance.
  • 3-Dimensional scoring: Theme Heat, Lifecycle maturity, and Confidence.
  • Uptrend integration with sector uptrend data to contextualize breadth and momentum.
  • Flexible data sources: FINVIZ Elite/public, optional FMP data, and narrative validation.
  • Use cases: identify hot and lagging market narratives, assess lifecycle stages, and select proxy exposures via proxy ETFs.

Quick Start

Run theme detection on the latest market data to generate a ranked themes dashboard.

Frequently Asked Questions about theme-detector

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

FAQPage Schema
How do I detect current market themes using FINVIZ sector data?▼

Market theme detection aggregates FINVIZ sector and industry performance data into a synthetic heat map. This approach ranks trending narratives by computing momentum, volume, uptrend signals, and breadth across sectors to identify bullish and bearish rotations.

What is thematic lifecycle analysis and how does it rank market narratives?▼

Thematic lifecycle analysis scores market narratives across three dimensions: heat, lifecycle maturity, and confidence. It cross-references sector momentum and breadth to determine whether a trending theme is emerging, peaking, or fading.

Can I use FINVIZ public data for sector rotation analysis or do I need an Elite subscription?▼

Sector rotation analysis supports both FINVIZ Elite and public data sources for computing theme momentum. Optional FMP metrics can further enhance the volume and uptrend signals integrated into the synthetic heat map output.

How do I identify proxy ETFs for hot market narratives?▼

Proxy ETFs are identified by ranking current market themes through cross-sector momentum and lifecycle maturity analysis. The resulting dashboard highlights trending bullish and bearish narratives with associated confidence scores for selecting targeted thematic exposures.

Does this approach require yfinance and pandas to compute momentum signals?▼

Computing momentum signals relies on pandas and numpy for data processing, while yfinance and finvizfinance retrieve sector performance. These dependencies aggregate industry data to evaluate uptrend integration and market breadth for theme ranking.

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