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 format

• end_date (optional): End date in YYYY-MM-DD format

• limit (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 symbols

• limit (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 symbols

• metrics (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