yfinance-data
Fetch financial and market data with the yfinance Python library (Yahoo Finance). Use this skill whenever the user wants stock data: current quotes and price history, financial statements (income statement, balance sheet, cash flow), options chains, dividends and splits, earnings and analyst estimates, price targets and ratings, institutional and insider holdings, news, multi-ticker comparisons, stock screens, or sector and industry data. Use it even when the user gives only a ticker symbol (AAPL, MSFT, TSLA) and the intent has to be inferred. For earnings previews or recaps, estimate revisions, valuation, correlation, liquidity, or ETF premium analysis, prefer the dedicated skill.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/himself65/finance-skills --skill yfinance-data- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads yfinance-data automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
Security audits
Independent scans of the skill's instructions and bundled files.
SKILL.md
The instructions your agent reads when the skill is triggered.
yfinance Data Skill
If your host has not already executed the shell probes below (for example, in Codex), run the commands inside the ! wrappers with its shell tool before choosing a setup path. Use the actual output; if shell access is unavailable, report that limitation.
Fetches financial and market data from Yahoo Finance using the yfinance Python library.
Important: yfinance is not affiliated with Yahoo, Inc. Data is for research and educational purposes.
Step 1: Ensure yfinance Is Available
Current environment status:
!`python3 -c "exec('try:\n import yfinance\n print(\'yfinance \' + yfinance.__version__ + \' installed\')\nexcept Exception:\n print(\'YFINANCE_NOT_INSTALLED\')')"`
If YFINANCE_NOT_INSTALLED, install it before running any code:
import subprocess, sys
subprocess.check_call([sys.executable, "-m", "pip", "install", "-q", "yfinance"])
If yfinance is already installed, skip the install step and proceed directly.
Step 2: Identify What the User Needs
Match the user's request to one or more data categories below, then use the corresponding code from references/api_reference.md.
| User Request | Data Category | Primary Method |
|---|---|---|
| Stock price, quote | Current price | ticker.info or ticker.fast_info |
| Price history, chart data | Historical OHLCV | ticker.history() or yf.download() |
| Balance sheet | Financial statements | ticker.balance_sheet |
| Income statement, revenue | Financial statements | ticker.income_stmt |
| Cash flow | Financial statements | ticker.cashflow |
| Dividends | Corporate actions | ticker.dividends |
| Stock splits | Corporate actions | ticker.splits |
| Options chain, calls, puts | Options data | ticker.option_chain() |
| Earnings, EPS | Analysis | ticker.earnings_history |
| Analyst price targets | Analysis | ticker.analyst_price_targets |
| Recommendations, ratings | Analysis | ticker.recommendations |
| Upgrades/downgrades | Analysis | ticker.upgrades_downgrades |
| Institutional holders | Ownership | ticker.institutional_holders |
| Insider transactions | Ownership | ticker.insider_transactions |
| Company overview, sector | General info | ticker.info |
| Compare multiple stocks | Bulk download | yf.download() |
| Screen/filter stocks | Screener | yf.screen() + yf.EquityQuery |
| Sector/industry data | Market data | yf.Sector / yf.Industry |
| News | News | ticker.news |
Step 3: Write and Execute the Code
General pattern
import yfinance as yf
ticker = yf.Ticker("AAPL")
# ... use the appropriate method from the reference
Key rules
- Always wrap in try/except — Yahoo Finance may rate-limit or return empty data
- Use
yf.download()for multi-ticker comparisons — it's faster with multi-threading - For options, list expiration dates first with
ticker.optionsbefore callingticker.option_chain(date) - For quarterly data, use
quarterly_prefix:ticker.quarterly_income_stmt,ticker.quarterly_balance_sheet,ticker.quarterly_cashflow - For large date ranges, be mindful of intraday limits — 1m data only goes back ~7 days, 1h data ~730 days
- Print DataFrames clearly — use
.to_string()or.to_markdown()for readability, or select key columns - Timezone handling — yfinance returns tz-aware datetime indices (e.g.,
America/New_York). When comparing dates, always usepd.Timestamp(..., tz=...)or strip timezones with.tz_localize(None). See the reference file for details.
Valid periods and intervals
| Periods | 1d, 5d, 1mo, 3mo, 6mo, 1y, 2y, 5y, 10y, ytd, max |
|---|---|
| Intervals | 1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 1d, 5d, 1wk, 1mo, 3mo |
Step 4: Present the Data
Answer with the numbers the user asked for first, then the supporting table (markdown, or a trimmed DataFrame with the key columns). Call out anything notable in the data — an earnings beat or miss, unusual volume, a dividend change — and add context such as sector averages, historical ranges, or analyst consensus where it changes how the numbers read. If the user wants a chart, pair the data with a visualization.
Reference Files
references/api_reference.md— Complete yfinance API reference with code examples for every data category
Read the reference file when you need exact method signatures or edge case handling.
FAQ
What does the yfinance-data skill do?
Fetch financial and market data with the yfinance Python library (Yahoo Finance). Use this skill whenever the user wants stock data: current quotes and price history, financial statements (income statement, balance sheet, cash flow), options chains, dividends and splits, earnings and analyst estimates, price targets and ratings, institutional and insider holdings, news, multi-ticker comparisons, stock screens, or sector and industry data. Use it even when the user gives only a ticker symbol (AAPL, MSFT, TSLA) and the intent has to be inferred. For earnings previews or recaps, estimate revisions, valuation, correlation, liquidity, or ETF premium analysis, prefer the dedicated skill.
How do I install yfinance-data?
Run npx skills add https://github.com/himself65/finance-skills --skill yfinance-data in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/yfinance-data/ (personal) or .claude/skills/yfinance-data/ (project).
Which AI agents can use yfinance-data?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is yfinance-data safe to install?
Security partners have reviewed it: Gen Agent Trust Hub passed; Socket passed; Snyk flagged items to review; Runlayer passed; ZeroLeaks passed. As with any skill, read the SKILL.md and bundled scripts before installing.
Who maintains yfinance-data?
It is published by himself65 in himself65/finance-skills. It has 3,914 recorded installs.
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