Financial Data Fetcher
SkillCommerce & financeFetches real-time and historical market data, financial news, and fundamental data for trading decisions
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Financial Data Fetcher skill
What this skill tells your AI
The instructions your AI receives, as published by gracefullight/stock-checker in .agents/skills/Financial Data Fetcher/SKILL.md and read by ahel’s review.
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 30
2. 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
Signals
- GitHub stars
- 44
- Forks
- 9
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
financial-data-fetcher- Source
- github.com/gracefullight/stock-checker