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Yahoo Finance market data downloader. Stock prices, options chains, fundamentals, dividends, splits, earnings, institutional holders, and financial statements. Quick data ingestion for quant research and backtesting.
Passed 16 of 22 test cases with the skill, and 14 of 22 without it.
and 1 more in the full report
3 fixed13 passed either way5 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
How do I fetch Microsoft daily price data from January 1, 2024 to December 31, 2024 into a DataFrame using Python without writing custom web scrapers?
| Checked | Without skill | With skill |
|---|---|---|
| Calls download with ticker symbol MSFT | Passed | Passed |
| Passes start parameter set to 2024-01-01 | Passed | Passed |
| Passes end parameter set to 2024-12-31 | Missed | Passed |
The instructions your model reads when the skill loads.
yfinance downloads Yahoo Finance market data: stock prices, options chains, fundamentals, dividends, splits, earnings, institutional holders, and financial statements. The fastest path from ticker symbol to pandas DataFrame for quant research and backtesting.
uv pip install yfinance
import yfinance as yf
msft = yf.download("MSFT", start="2024-01-01", end="2024-12-31")
print(msft.head())
ticker = yf.Ticker("AAPL")
info = ticker.info
print(f"Market cap: {info['marketCap']:,}")
print(f"PE ratio: {info['trailingPE']}")
print(f"Dividend yield: {info.get('dividendYield', 0)*100:.2f}%")
print(ticker.balance_sheet)
print(ticker.financials)
opt = ticker.option_chain(ticker.options[0])
print(opt.calls[["strike", "lastPrice", "impliedVolatility", "volume"]].head())
print(opt.puts[["strike", "lastPrice", "impliedVolatility", "volume"]].head())
test cases passed, vs 14 / 22 without
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