yfinance Data FetcherFinance Skill

A yfinance data fetching skill. 4-step process: (1) ensure yfinance is available (auto-install via pip if missing); (2) identify what the user needs via data category routing table (current price → ticker.info/fast_info, historical OHLCV → ticker.history()/yf.download(), balance sheet → ticker.balance_sheet, income statement → ticker.income_stmt, cash flow → ticker.cashflow, dividends → ticker.dividends, splits → ticker.splits, options → ticker.option_chain(), earnings → ticker.earnings_history, analyst targets → ticker.analyst_price_targets, recommendations → ticker.recommendations, upgrades/downgrades → ticker.upgrades_downgrades, institutional holders → ticker.institutional_holders, insider transactions → ticker.insider_transactions, screener → yf.Screener + yf.EquityQuery, sector/industry → yf.Sector/yf.Industry, news → ticker.news); (3) write and execute code following 7 key rules (always try/except, use yf.download() for multi-ticker, list options expirations first, use quarterly_ prefix for quarterly data, mind intraday limits — 1m only 7 days back, 1h 730 days, print DataFrames clearly with to_string()/to_markdown(), handle tz-aware datetime indices); (4) present data clearly (summarize key numbers, show tabular data, highlight notable items, provide context). Valid periods: 1d/5d/1mo/3mo/6mo/1y/2y/5y/10y/ytd/max. Valid intervals: 1m/2m/5m/15m/30m/60m/90m/1h/1d/5d/1wk/1mo/3mo. Includes comprehensive API reference file with code examples for every data category. Uses yfinance (required). Python 3.8+. Works on all platforms.

Snapshot quality

88/100

Snapshot risk

Medium

Audit conclusion

Needs review