OHLCV stands for open, high, low, close, and volume—the core price and trading activity metrics for a stock.

How do period and interval differ?

Period defines the time span (e.g., 1mo, 5y) while interval defines data granularity (e.g., 1d, 1m).

price-history

Scanned

npx machina-cli add skill staskh/trading_skills/price-history --openclaw

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SKILL.md

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Price History

Fetch historical OHLCV data from Yahoo Finance.

Instructions

Note: If uv is not installed or pyproject.toml is not found, replace uv run python with python in all commands below.

uv run python scripts/history.py SYMBOL [--period PERIOD] [--interval INTERVAL]

Arguments

SYMBOL - Ticker symbol
--period - Time period: 1d, 5d, 1mo, 3mo, 6mo, 1y, 2y, 5y, 10y, ytd, max (default: 1mo)
--interval - Data interval: 1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 1d, 5d, 1wk, 1mo (default: 1d)

Output

Returns JSON with:

symbol - Ticker
period - Requested period
interval - Data interval
data - Array of {date, open, high, low, close, volume}

Summarize key price movements, highs/lows, and trends.

Dependencies

yfinance

Source

git clone https://github.com/staskh/trading_skills/blob/main/.claude/skills/price-history/SKILL.mdView on GitHub

Overview

Fetch historical OHLCV data for a stock from Yahoo Finance. It returns a structured JSON payload including symbol, period, interval, and a data array of date, open, high, low, close, and volume to support charting and analysis.

How This Skill Works

It runs a Python script that queries Yahoo Finance for the specified SYMBOL, period, and interval. If uv is available, use the command uv run python scripts/history.py SYMBOL [--period PERIOD] [--interval INTERVAL]; otherwise run python scripts/history.py SYMBOL [--period PERIOD] [--interval INTERVAL]. The response is JSON with symbol, period, interval, and data: an array of {date, open, high, low, close, volume}.

When to Use It

When a user asks for price history or past performance of a stock
When you need data for charting, backtesting, or dashboards
When you want a specific data granularity (intraday or daily) and period (max, 5y, ytd, etc.)
When analyzing highs, lows and trends over a time range
When preparing a report that includes OHLCV summaries and trend insights

Quick Start

Step 1: Ensure uv is installed and pyproject.toml exists in your project
Step 2: Run: uv run python scripts/history.py SYMBOL --period PERIOD --interval INTERVAL
Step 3: Parse the returned JSON to feed your chart or analysis

Best Practices

Verify SYMBOL is correct and the requested period/interval match your analysis needs
Prefer longer periods with coarser intervals for trend analysis and shorter periods with finer intervals for intraday insights
Expect gaps on holidays or missing data around stock splits; plan to handle in post-processing
Validate the returned data structure and convert date fields to your local timezone if needed
Cache repeated requests to reduce latency and Yahoo Finance calls

Example Use Cases

Fetch 1mo of daily OHLCV for AAPL to plot a short-term chart
Retrieve 5y of daily data for MSFT to observe long-term performance
Get intraday 5m data for TSLA for today’s trading session
Compare GOOG price movement across the last quarter (90d) to identify trends
Export AAPL data for a dashboard visualization

Frequently Asked Questions

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