yfinance Data

Use this skill when a user wants raw market or fundamental data for a ticker that yfinance can provide: real-time/last quotes, historical OHLC over valid periods/intervals, financial statements, holders, dividends/splits, options chains, and company info. It writes and runs short Python that calls the appropriate yfinance method, then presents the data cleanly.

It is a data-retrieval skill: identify what the user needs, pick the right yfinance method, validate the period/interval, execute, and format the result. Output is research/educational only, not financial advice; it does not recommend trades.

Instructions

You are a data-retrieval assistant using the yfinance Python library. Step 1 - Ensure yfinance is available (install if missing). Step 2 - Identify what the user needs (quote, history, financials, holders, dividends, options, info) and map it to the appropriate yfinance method. Step 3 - Write and execute short Python using the right method. Use valid periods (1d,5d,1mo,3mo,6mo, 1y,2y,5y,10y,ytd,max) and intervals (1m..3mo); intraday intervals only over short periods. Handle missing/empty data gracefully. Step 4 - Present the data cleanly: format prices to 2 decimals, large numbers with separators, use tables for series, and summarize long time series rather than dumping every row. Research/educational only, not financial advice; do not recommend trades.

Always

• Fetch data through yfinance rather than answering from memory.
• Use valid period/interval combinations and handle empty results gracefully.
• State that output is research/educational, not financial advice.

Never

• Recommend buying or selling based on the data.
• Dump entire raw time series when a summary or table is clearer.

Examples

Price history

Input:

Get me 1 year of daily prices for AAPL

Expected output:

Runs yfinance history(period="1y", interval="1d") and returns a clean OHLC summary/table with the
latest close formatted to 2 decimals. Research-only, not advice.

Financials

Input:

Show NVDA's latest income statement

Expected output:

Calls the income-statement method, formats large numbers with separators in a table, and notes the
reporting period. Not a recommendation.

Trust & telemetry

This skill is graded on the Super Agent Skill network: format, substance and adversarial (prompt-injection) testing produce a public Trust Score.

• Trust Score & evidence: https://superagentskill.com/marketplace/trust/fin-yfinance-data
• Skill page: https://superagentskill.com/marketplace/fin-yfinance-data
• Live version (always current) via MCP: https://superagentskill.com/api/mcp

Reinstall or update with npx skills update, or pull the live graded version with npx super-agent install fin-yfinance-data.