Agent skill · data analytics · tradermonty
theme-detector
Detect and analyze trending market themes across sectors. Use when user asks about current market themes, trending sectors, sector rotation, thematic investing, what themes are hot or cold, or wants to identify bullish and bearish market narratives with lifecycle analysis.
Why this skill is useful
Provides domain-specific algorithms for detecting and analyzing market themes that the AI wouldn't generate on its own.
What it needs
Requires beautifulsoup4, lxml, numpy, pandas, python, requests, yfinance installed locally. About 10k tokens when loaded. Last updated 2026-08-06. 2,581 stars on the source repository.
What this skill does
Theme Detector Overview This skill detects and ranks trending market themes by analyzing cross-sector momentum, volume, and breadth signals. It identifies both bullish (upward momentum) and bearish (downward pressure) themes, assesses lifecycle maturity (Emerging/Accelerating/Trending/Mature/Exhausting), and provides a confidence score combining quantitative data with narrative analysis. 3-Dimensional Scoring Model: 1. Theme Heat (0-100): Direction-neutral strength of the theme (momentum, volume, uptrend ratio, breadth) 2. Lifecycle Maturity: Stage classification (Emerging / Accelerating / Trending / Mature / Exhausting) based on duration, extremity clustering, valuation, and ETF proliferation 3. Confidence (Low / Medium / High): Reliability of the detection, combining quantitative breadth with narrative confirmation. Script output is capped at Medium; Claude's WebSearch narrative confirmation step can elevate to High. 4. Stock Leadership: Optional daily scan-hit evidence from 5D+20%, EP9M, range expansion, new highs, and high-RS stocks. When supplied, this is blended into Theme Heat v2; when absent, it lowers confidence coverage but does not force leadership to zero. 5. Theme Match Quality: Specificity of the theme match from industry participation, explicit stock-basket hits, proxy ETF confirmation, and optional offline narrative scores. This is evidence quality, not a trade recommendation. Key Features: Cross-sector theme detection using FINVIZ industry data Direction-aware scoring (bullish and bearish themes) Lifecycle maturity assessment to identify crowded vs. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills tradermonty/theme-detector