A sophisticated financial tool that converts natural language queries into precise stock selection filters using Eastmoney official data.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install em-stockpick
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 em-stockpick 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 DFCF_StockPick?
DFCF_StockPick is a specialized module designed for the Openclaw Skills framework that bridges the gap between complex financial data and intuitive user intent. By leveraging Python to interface directly with Eastmoney official web services, it allows developers and investors to execute highly specific market queries using simple human language.
This skill eliminates the need to manually navigate complex filter interfaces or write custom scrapers for technical indicators. Whether you are looking for fundamental data, technical breakouts, or specific sector performance, DFCF_StockPick provides a streamlined path to actionable market intelligence within the Openclaw Skills environment.
DFCF_StockPick Use Cases
- Identifying high-value stocks by filtering for specific price thresholds (e.g., stocks over 1000 CNY).
- Analyzing industry leaders in the Hong Kong market using natural language descriptions.
- Finding high-yield or low-premium opportunities in the Convertible Bond (CB) market.
- Rapidly identifying the top-performing market sectors or ETFs based on daily price action.
- Conducting deep fundamental research by combining PE ratios with growth constraints across different stock exchanges.
How DFCF_StockPick Works
- The user provides a natural language query specifying the desired financial assets and criteria.
- The skill processes the input and maps the query to the appropriate Eastmoney selection type (A-Shares, HK Stocks, ETF, etc.).
- An internal Python engine communicates with the Eastmoney official website backend to apply the filter logic.
- The system retrieves the real-time or near-real-time list of assets matching the specified conditions.
- Structured financial data is returned to the user or calling agent for further analysis.
DFCF_StockPick Setup
To integrate this capability into your project, ensure you have the necessary environment configured for Openclaw Skills. You can run the selector directly via the CLI:
# Example: Selecting A-shares with price > 100 CNY and showing their sectors
python -m scripts.em_stock_selector --query "股价大于100元的股票；涨跌幅；所属板块" --select-type A股
DFCF_StockPick Data Schema & Taxonomy
The skill utilizes a structured parameter system to ensure high accuracy within the Openclaw Skills ecosystem:
| Parameter | Type | Description |
|---|---|---|
--query |
String | The natural language condition (e.g., 'Stocks with PE ratio < 15') |
--select-type |
Enum | The asset domain: A股 (A-Shares), 港股 (HK), ETF, 可转债 (CB), or 板块 (Sectors) |
Results are typically returned as a list of stock codes, names, and the specific metrics requested in the query.
DFCF_StockPick Advanced Features
- Multi-asset support covering A-shares, Hong Kong stocks, ETFs, and Convertible Bonds.
- Complex condition stacking (combining fundamental indicators like PE with technical indicators like price action).
- Seamless integration with the Openclaw Skills automated workflow for daily market reports.
- Direct backend access to official Eastmoney data feeds for high reliability.
SKILL.md
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