Aggregate FINVIZ sector performance, ETF signals, and uptrend data to rank market themes.
npx skills add https://github.com/kavi-lin/stock --skill theme-detector-kavi-lin
Please help me install this Agent Skill. Skill: theme-detector Source: https://github.com/kavi-lin/stock/tree/main/skills/theme-detector Command: npx skills add https://github.com/kavi-lin/stock --skill theme-detector-kavi-lin
Quantifies and ranks market themes by aggregating sector performance, uptrend signals, and ETF activity to help investors identify where money is flowing.
Run python3 skills/theme-detector/scripts/theme_detector.py to generate reports.
High-intent search queries and answers about installing and using this skill.
FINVIZ sector performance, ETF signals, and uptrend data are aggregated to detect and rank market themes. The tool applies momentum, volume, breadth, and lifecycle analysis to identify bullish and bearish sectors within US equities.
Yes, sector rotation and bullish themes can be identified using yfinance and pandas. The Skill leverages these dependencies alongside FINVIZ data to calculate uptrend signals and output structured JSON and Markdown reports.
No, a FINVIZ Elite subscription is not required. The Skill supports both optional FINVIZ Elite and public mode, alongside optional FMP data, requiring only Python 3.7+ and the included dependencies to function.
The best way to quantify sector momentum and breadth for US equities is using a structured 3D scoring framework. This approach aggregates FINVIZ sector performance and ETF activity to rank market themes and identify where capital is flowing.
Run the included Python script to generate JSON and Markdown reports for thematic investing analysis. The script processes uptrend data and ETF signals to produce shareable insights that guide investment decisions based on sector rotation.
FINVIZ sector performance signals alone may miss market theme rotation if they lack ETF activity and uptrend data context. This Skill resolves limitations by applying a 3D scoring framework that combines momentum, volume, and breadth analysis.
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