stock-screener
Filter and screen stocks by financial metrics like P/E ratio, market cap, dividend yield, and growth rates. Analyze and compare stocks from CSV data.
npx skills add majiayu000/claude-skill-registry --skill stock-screener-dkyazzentwatwa-chatgpt-skills-1375fb54 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Stock Screener Filter stocks by financial metrics and perform comparative analysis. ## Features - **Multi-Metric Filtering**: P/E, P/B, market cap, dividend yield, etc. - **Custom Screens**: Save and reuse filter combinations - **Comparative Analysis**: Side-by-side stock comparison - **Sector Analysis**: Group and analyze by sector - **Ranking**: Score and rank stocks by criteria - **Export**: CSV, JSON, formatted reports ## Quick Start ```python from stock_screener import StockScreener screener = StockScreener() # Load stock data screener.load_csv("stocks.csv") # Apply filters results = screener.filter( pe_ratio=(0, 20), market_cap_min=1e9, dividend_yield_min=2.0 ) print(results) ``` ## CLI Usage ```bash # Basic screening python stock_screener.py --input stocks.csv --pe-max 20 --div-min 2.0 # Multiple filters python stock_screener.py --input stocks.csv --pe 5 25 --pb-max 3 --cap-min 1B # Sector filter python stock_screener.py --input stocks.csv --sector Technology --pe-max 30 # Rank by metric python stock_screener.py --input stocks.csv --rank-by dividend_yield --top 20 # Compare specific stocks python stock_screener.py --input stocks.csv --compare AAPL MSFT GOOGL # Export resul
- Features
- Quick Start
- CLI Usage
- Input Format
- Stock CSV
- API Reference
- StockScreener Class
- Filtering Criteria
- Valuation Metrics
- Size Metrics
- Income Metrics
- Growth Metrics
- Quality Metrics
- Preset Screens
Basic screening python stock_screener.py --input stocks.csv --pe-max 20 --div-min 2.0 Multiple filters python stock_screener.py --input stocks.csv --pe 5 25 --pb-max 3 --cap-min 1B Sector filter python stock_screener.py --input stocks.csv --sector Technology --pe-max 30 Rank by metric python stock_screener.py --input stocks.csv --rank-by dividend_yield --top 20 Compare specific stocks python stock_screener.py --input stocks.csv --compare AAPL MSFT GOOGL
What does the stock-screener skill do?
Filter and screen stocks by financial metrics like P/E ratio, market cap, dividend yield, and growth rates. Analyze and compare stocks from CSV data.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill stock-screener-dkyazzentwatwa-chatgpt-skills-1375fb54 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.