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" ]