A comprehensive market intelligence tool for tracking real-time stock prices and financial metrics across global exchanges.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install skills-public
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install skills-public using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Stock Query?
The Stock Query skill is a powerful financial data integration designed for Openclaw Skills. It enables AI agents to retrieve and interpret real-time market data across major global exchanges, including the Shanghai and Shenzhen Stock Exchanges (A-shares), the Hong Kong Stock Exchange (HKEX), and US markets like NASDAQ and NYSE.
By leveraging advanced web search and data extraction, this skill transforms natural language queries into structured financial insights. It is essential for users needing immediate updates on equity performance, price movements, and trading volumes without leaving their AI-driven workflow.
Stock Query Use Cases
- Monitoring real-time price fluctuations for specific tickers like AAPL or 600519.
- Comparing market performance across different regions such as US and Hong Kong markets.
- Retrieving detailed financial snapshots including daily highs, lows, and trading volumes.
- Automating financial research tasks by integrating stock data into broader analysis reports.
How Stock Query Works
- The agent identifies the stock ticker or company name within a natural language request.
- It triggers a search protocol to fetch the most recent market data from reliable financial web sources.
- The skill parses the raw data into a structured format containing price, change percentage, and volume.
- It delivers a comprehensive summary to the user, accounting for market-specific nuances like trading hours and data delays.
Stock Query Setup
To integrate this capability into your environment, ensure the skill files are placed in your local directory and accessible via the following path:
# Manual query for testing or debugging
python /root/.openclaw/workspace/skills/stock-query/scripts/stock_query.py <ticker_code>
Stock Query Data Schema & Taxonomy
The skill returns a structured dataset for each query to ensure consistency across Openclaw Skills. The following table describes the primary data points provided:
| Attribute | Description |
|---|---|
| Stock Name/Code | The official ticker symbol and company name. |
| Current Price | The most recent traded price in the local currency. |
| Change (%) | The price movement relative to the previous close. |
| High/Low | The intraday peak and floor prices. |
| Volume/Turnover | The total number of shares traded and total value. |
| Market Cap | The total market valuation (where available). |
Stock Query Advanced Features
- Multi-market support covering Mainland China, Hong Kong, and United States exchanges.
- Natural language processing (NLP) to resolve company names to their respective ticker symbols automatically.
- Intelligent handling of market status, providing the last closing price during off-market hours.
- Real-time data fetching with a specialized 15-minute delay buffer for US equities to ensure data reliability.
SKILL.md
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