Market Quote Desk

    1

    Get market data without API keys through Yahoo Finance endpoints wrapped by a small CLI: real-time quotes, OHLC history, ticker search, symbol comparisons, movi

    $5

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    Works with the AI tools you already use

    CClaude CodeCCursorCCodex CLIGGitHub CopilotGGemini CLIVVS CodeWWindsurfMManus+14 more

    See it in action

    You say

    Compare the YTD returns of AAPL, MSFT, and NVDA and export AAPL's 6-month daily history to a file called tech_data.csv.

    Your agent does

    Comparison (YTD Return): AAPL: +12.4% MSFT: +15.8% NVDA: +142.1% Successfully fetched 6 months of daily OHLC data for AAPL. File saved: tech_data.csv (126 rows).

    What you get

    Export adjusted OHLC history to CSV for backtesting and analysis.Compare YTD returns and volatility across multiple tickers in a single table.Calculate 50-day and 200-day moving averages for trend identification.Track total USD value of mixed stock and crypto portfolios via CLI.

    About this skill

    The problem

    Getting clean market data often requires expensive API keys, complex SDKs, or dealing with rate-limited scrapers. Developers need a way to pull quotes, history, and basic technical indicators without the overhead of enterprise financial platforms.

    What it does

    • Fetches real-time price snapshots, volume, and market cap for stocks, crypto, and FX pairs.
    • Exports OHLC history to CSV with adjusted close prices for accurate backtesting.
    • Calculates simple moving averages (SMA) across custom windows directly from price history.
    • Generates side-by-side performance comparisons using returns or volatility metrics.
    • Manages a lightweight local portfolio tracker to calculate total USD value across assets.

    Frameworks & tools

    Python, yquote CLI, Yahoo Finance public endpoints.

    Why this beats prompting it yourself

    Manual prompting often results in hallucinated tickers or broken scraping logic when Yahoo Finance updates their DOM. This skill uses a dedicated CLI wrapper to ensure consistent data structures, proper CSV formatting for adj_close, and validated technical indicator math.

    Use cases

    • Generating CSV datasets for local charting or spreadsheet analysis.
    • Performing quick YTD return comparisons between competing equities.
    • Checking crypto and stock portfolio balances from the terminal.
    • Validating SMA crossovers for personal trading research.

    Known limitations

    Requires the yquote Python package installed. Not suitable for high-frequency trading, options Greeks, or streaming intraday data.

    stocks
    finance
    quotes
    crypto
    yahoo

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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