
Financial Data Fetcher
- 502 installs
- 41 repo stars
- Updated August 4, 2026
- gracefullight/stock-checker
financial-data-fetcher is an agent skill that pulls real-time stock prices, fundamentals, and market data into prototypes, pricing tools, or financial dashboards for developers.
About
financial-data-fetcher is a gracefullight/stock-checker agent skill that retrieves accurate real-time stock prices, company fundamentals, and broader market data for use in code prototypes, pricing engines, or financial dashboards. It helps backend and full-stack developers wire market feeds into applications without hand-rolling API client boilerplate for every ticker query. The skill reports 456 installs and rank 4 on skills.sh within the stock-checker repository. Invoke it when an agent session needs live quotes, fundamental ratios, or market snapshots embedded in Python, JavaScript, or API service code during feature development or data pipeline prototyping.
- Fetches live stock quotes, company fundamentals, and historical price data
- Returns structured JSON ready for agents, spreadsheets, or internal tools
- Supports major exchanges and tickers with minimal configuration
- Designed for indie builders validating financial features or pricing models
- 456 installs across solo-builder projects
Financial Data Fetcher by the numbers
- 502 all-time installs (skills.sh)
- Ranked #449 of 2,064 Data Science & ML skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 502 |
|---|---|
| repo stars | ★ 41 |
| Last updated | August 4, 2026 |
| Repository | gracefullight/stock-checker ↗ |
How do you fetch real-time stock prices in code?
Pull accurate real-time stock prices, fundamentals, and market data into prototypes, pricing tools, or financial dashboards.
Who is it for?
Developers building financial dashboards, pricing tools, or market-data prototypes who need programmatic stock quotes.
Skip if: Production trading systems requiring exchange-grade latency, compliance, or licensed brokerage execution.
When should I use this skill?
A developer needs live stock prices, fundamentals, or market data pulled into application code or a dashboard.
What you get
Stock price quotes, fundamental metrics, and market data payloads ready for dashboards or API responses.
- stock price quotes
- fundamental metrics
- market data API responses
By the numbers
- Reports 456 installs on skills.sh
- Ranks 4 in gracefullight/stock-checker on skills.sh
Files
Financial Data Fetcher Skill
Provides comprehensive market data access for AI trading agents.
Overview
This skill fetches:
- Real-time and historical OHLCV price data
- Financial news from multiple sources
- Fundamental data (P/E ratios, earnings, market cap)
- Market snapshots and quotes
Tools
1. get_price_data
Fetches historical or real-time price data for symbols.
Parameters:
symbols(required): List of ticker symbols (e.g., ["AAPL", "MSFT"])timeframe(optional): "1Min", "5Min", "1Hour", "1Day" (default: "1Day")start_date(optional): Start date in YYYY-MM-DD formatend_date(optional): End date in YYYY-MM-DD formatlimit(optional): Number of bars to fetch (default: 100)
Returns:
{
"success": true,
"data": {
"AAPL": [
{
"timestamp": "2025-10-30T09:30:00Z",
"open": 150.25,
"high": 151.50,
"low": 149.80,
"close": 151.00,
"volume": 5000000
}
]
}
}Usage:
python scripts/fetch_data.py get_price_data --symbols AAPL MSFT --timeframe 1Day --limit 302. get_latest_news
Fetches recent financial news for symbols.
Parameters:
symbols(required): List of ticker symbolslimit(optional): Number of news items (default: 10)sources(optional): News sources to query (default: all)
Returns:
{
"success": true,
"data": [
{
"symbol": "AAPL",
"headline": "Apple announces new product line",
"summary": "...",
"source": "Bloomberg",
"url": "https://...",
"published_at": "2025-10-30T08:00:00Z",
"sentiment": "positive"
}
]
}3. get_fundamentals
Fetches fundamental data for symbols.
Parameters:
symbols(required): List of ticker symbolsmetrics(optional): Specific metrics to fetch (default: all)
Returns:
{
"success": true,
"data": {
"AAPL": {
"market_cap": 3000000000000,
"pe_ratio": 28.5,
"eps": 6.42,
"dividend_yield": 0.52,
"beta": 1.2,
"52_week_high": 200.00,
"52_week_low": 120.00
}
}
}4. get_market_snapshot
Gets current market snapshot with real-time quotes.
Parameters:
symbols(required): List of ticker symbols
Returns:
{
"success": true,
"data": {
"AAPL": {
"price": 151.00,
"bid": 150.98,
"ask": 151.02,
"bid_size": 100,
"ask_size": 200,
"last_trade_time": "2025-10-30T15:59:59Z",
"volume": 50000000,
"vwap": 150.75
}
}
}Implementation
See scripts/fetch_data.py for full implementation using Alpaca API and yfinance.
Rate Limiting
- Alpaca API: 200 requests/minute
- News API: 25 requests/day (free tier)
- Caching: 5-minute cache for real-time data
Error Handling
All tools return consistent error format:
{
"success": false,
"error": "Error message",
"error_code": "INVALID_SYMBOL"
}Integration Example
from claude_skills import load_skill
skill = load_skill("financial_data_fetcher")
# Get price data
result = skill.get_price_data(
symbols=["AAPL", "MSFT"],
timeframe="1Day",
limit=30
)
if result["success"]:
prices = result["data"]
# Use in trading strategy{
"name": "financial-data-fetcher",
"repo": "IgorGanapolsky/trading",
"category": "devops",
"description": "Fetches real-time and historical market data, financial news, and fundamental data for trading decisions",
"source": "SkillsMP + GitHub Raw",
"downloaded_at": "2026-01-06T09:00:53.230669Z"
}
Related skills
How it compares
Pick financial-data-fetcher for quick market-data integration in app prototypes instead of full quantitative research or backtesting stacks.
FAQ
What data does financial-data-fetcher retrieve?
The financial-data-fetcher skill pulls real-time stock prices, company fundamentals, and market data for use in prototypes, pricing tools, and financial dashboards. It is published from gracefullight/stock-checker on skills.sh.
When should developers use financial-data-fetcher?
Developers should use financial-data-fetcher when building dashboards, pricing engines, or API endpoints that need programmatic stock quotes and fundamental metrics during active development in Claude Code or Cursor.