skillZs
★ LIVE SKILL TAGS ★
>>> LIVE SKILLS INDEX <<<
* OPEN SOURCE *
NO LOGIN, NO TRACKING
※ REAL INSTALL DATA ※
← back to all skills
gracefullight/stock-checker0 installs

Financial Data Fetcher

Fetches real-time and historical market data, financial news, and fundamental data for trading decisions

How do I install this agent skill?

npx skills add https://github.com/gracefullight/stock-checker --skill financial-data-fetcher
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubfail

    This skill is rated HIGH risk primarily due to its Indirect Prompt Injection surface. It fetches untrusted financial news content that could contain malicious instructions to manipulate trading decisions. Additionally, the skill's metadata is misleadingly categorized, and it relies on an untrusted repository.

  • Socketpass

    No alerts

  • Snykwarn

    Risk: MEDIUM · No issues

  • Runlayerwarn

    1/2 files flagged

  • ZeroLeakspass

    Score: 93/100 · 2 sections analyzed

What does this agent skill do?

Financial Data Fetcher Skill

Provides comprehensive market data access for AI trading agents.

Overview

This skill fetches:

  • Real-time and historical OHLCV price data
  • Financial news from multiple sources
  • Fundamental data (P/E ratios, earnings, market cap)
  • Market snapshots and quotes

Tools

1. get_price_data

Fetches historical or real-time price data for symbols.

Parameters:

  • symbols (required): List of ticker symbols (e.g., ["AAPL", "MSFT"])
  • timeframe (optional): "1Min", "5Min", "1Hour", "1Day" (default: "1Day")
  • start_date (optional): Start date in YYYY-MM-DD format
  • end_date (optional): End date in YYYY-MM-DD format
  • limit (optional): Number of bars to fetch (default: 100)

Returns:

{
  "success": true,
  "data": {
    "AAPL": [
      {
        "timestamp": "2025-10-30T09:30:00Z",
        "open": 150.25,
        "high": 151.50,
        "low": 149.80,
        "close": 151.00,
        "volume": 5000000
      }
    ]
  }
}

Usage:

python scripts/fetch_data.py get_price_data --symbols AAPL MSFT --timeframe 1Day --limit 30

2. get_latest_news

Fetches recent financial news for symbols.

Parameters:

  • symbols (required): List of ticker symbols
  • limit (optional): Number of news items (default: 10)
  • sources (optional): News sources to query (default: all)

Returns:

{
  "success": true,
  "data": [
    {
      "symbol": "AAPL",
      "headline": "Apple announces new product line",
      "summary": "...",
      "source": "Bloomberg",
      "url": "https://...",
      "published_at": "2025-10-30T08:00:00Z",
      "sentiment": "positive"
    }
  ]
}

3. get_fundamentals

Fetches fundamental data for symbols.

Parameters:

  • symbols (required): List of ticker symbols
  • metrics (optional): Specific metrics to fetch (default: all)

Returns:

{
  "success": true,
  "data": {
    "AAPL": {
      "market_cap": 3000000000000,
      "pe_ratio": 28.5,
      "eps": 6.42,
      "dividend_yield": 0.52,
      "beta": 1.2,
      "52_week_high": 200.00,
      "52_week_low": 120.00
    }
  }
}

4. get_market_snapshot

Gets current market snapshot with real-time quotes.

Parameters:

  • symbols (required): List of ticker symbols

Returns:

{
  "success": true,
  "data": {
    "AAPL": {
      "price": 151.00,
      "bid": 150.98,
      "ask": 151.02,
      "bid_size": 100,
      "ask_size": 200,
      "last_trade_time": "2025-10-30T15:59:59Z",
      "volume": 50000000,
      "vwap": 150.75
    }
  }
}

Implementation

See scripts/fetch_data.py for full implementation using Alpaca API and yfinance.

Rate Limiting

  • Alpaca API: 200 requests/minute
  • News API: 25 requests/day (free tier)
  • Caching: 5-minute cache for real-time data

Error Handling

All tools return consistent error format:

{
  "success": false,
  "error": "Error message",
  "error_code": "INVALID_SYMBOL"
}

Integration Example

from claude_skills import load_skill

skill = load_skill("financial_data_fetcher")

# Get price data
result = skill.get_price_data(
    symbols=["AAPL", "MSFT"],
    timeframe="1Day",
    limit=30
)

if result["success"]:
    prices = result["data"]
    # Use in trading strategy

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

<a href="https://skillzs.dev/skills/gracefullight/stock-checker/financial-data-fetcher">View Financial Data Fetcher on skillZs</a>