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findata-toolkit-us

Fetches live US market data and SEC filings for integrated investment analytics.

271|41|Updated Feb 6, 2026
Search Tags:#finance#data-analysis#risk-analysis#yfinance#stock-data#macro-data#sec-edgar
One-click install
npx skills add https://github.com/Geeksfino/finskills --skill findata-toolkit-us
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: findata-toolkit-us
Source: https://github.com/Geeksfino/finskills/tree/main/US-market/findata-toolkit
Command: npx skills add https://github.com/Geeksfino/finskills --skill findata-toolkit-us

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires yfinance, pandas, numpy, scipy, requests, pandas-datareader, yaml, and includes scripts (resource) components.

What problem does it solve?

Financial analysts and developers often need real-time US market data and integrated analytics to ground investment decisions. This toolkit provides a self-contained set of scripts to fetch live data (stock prices, SEC filings, insider trades) and run quantitative calculations across portfolios and macro context.

Core Features & Use Cases

  • Live stock quotes, fundamentals, and history via yfinance
  • SEC EDGAR insider trades and company filings
  • Financial calculators: DuPont, Z-Score, Beneish M-Score, Piotroski F-Score, earnings quality, and working capital
  • Portfolio analytics: VaR, stress testing, health scoring
  • Multi-factor screening and macro indicators (FRED)

Quick Start

Run the stock_data script for a ticker to fetch live data and view core metrics.

Frequently Asked Questions about findata-toolkit-us

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

FAQPage Schema
How do I fetch live stock data and run financial analysis using Python?▼

You can fetch live stock data and run financial analysis using Python by executing script-based workflows that leverage yfinance for quotes and fundamentals, SEC EDGAR for insider trades, and FRED for macro indicators to ground investment decisions.

Can I calculate Piotroski F-Score and Beneish M-Score from yfinance fundamentals?▼

Yes, you can calculate Piotroski F-Score, Beneish M-Score, DuPont, and Z-Score using built-in financial calculators that process fundamental data extracted from yfinance to deliver structured quantitative outputs.

Does this toolkit support SEC EDGAR insider trades and company filings retrieval?▼

Yes, the toolkit supports SEC EDGAR data retrieval by using open-source requests to extract live insider trades and company filings, which are then processed with pandas and numpy for structured analytics.

What is the best way to perform portfolio VaR and stress testing on US market data?▼

The best way to perform portfolio VaR and stress testing on US market data is to use integrated analytics scripts that apply scipy and numpy calculations to live stock history fetched via pandas-datareader and yfinance.

Do I need pandas-datareader to fetch FRED macro indicators for multi-factor screening?▼

Yes, you need pandas-datareader alongside requests to fetch FRED macro indicators, which are then combined with yfinance stock data in pandas DataFrames to execute multi-factor screening and portfolio health scoring.

Are there limitations when using yfinance for real-time US market data and portfolio analytics?▼

A limitation of using yfinance for portfolio analytics is its dependency on open-source data feeds, meaning real-time US market data availability and frequency may vary compared to paid terminal APIs for stress testing.

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