A powerful financial data retrieval tool for the Chinese A-share market leveraging the pywencai library.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install pywencaistock
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 pywencaistock 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 PyWenCai Stock Data?
The PyWenCai Stock Data skill provides a seamless interface to access the Tonghuashun iWencai stock data API. By integrating this capability into Openclaw Skills, developers and analysts can programmatically retrieve a wide range of market information, from real-time price action to deep fundamental financial metrics. It is specifically optimized for the Chinese equity market, making it an essential tool for quantitative analysis and automated trading research.
This skill transforms natural language queries into structured data, allowing users to interact with complex financial databases without needing to manage raw API endpoints manually. Whether you are tracking sector trends or performing deep-dive financial audits on specific companies, this addition to the Openclaw Skills ecosystem streamlines the entire data acquisition workflow.
PyWenCai Stock Data Use Cases
- Real-time monitoring of A-share market movements including daily price limits and top gainers.
- Automated screening of stocks based on fundamental financial indicators such as ROE, PE ratios, and net profit growth.
- Tracking institutional investor activity through Dragon-Tiger lists and main force fund flow analysis.
- Researching specific industry concepts and emerging stock sectors using conceptual keyword searches.
How PyWenCai Stock Data Works
- The skill receives a search query and optional parameters like pagination or sorting.
- It interfaces with the pywencai library to communicate with the Tonghuashun iWencai backend.
- The natural language query is processed to retrieve the relevant market or financial data.
- Resulting data is automatically parsed and organized into a structured format.
- The skill returns a pandas DataFrame, enabling immediate data manipulation or export within your environment.
PyWenCai Stock Data Setup
To use this skill within the Openclaw Skills framework, you need to install the underlying library and its dependencies:
# Install the pywencai library
pip install pywencai
# Recommended: Install pandas for advanced data handling
pip install pandas
PyWenCai Stock Data Data Schema & Taxonomy
The skill returns data as a pandas DataFrame. Because the queries are dynamic, the columns in the resulting table will change based on your search intent. Below is a general taxonomy of returned data:
| Category | Common Fields |
|---|---|
| Basic Info | Stock Code, Stock Name, Market Segment |
| Market Stats | Current Price, Change %, Turnover Rate, Volume |
| Financials | Net Profit, PE (TTM), ROE, Total Assets |
| Sentiment | Dragon-Tiger List data, Institutional Net Buy, Main Force Inflow |
PyWenCai Stock Data Advanced Features
- Automatic result merging using the loop parameter to bypass single-page result limits.
- Advanced server-side sorting by specifying sort_key and sort_order within the search function.
- Configurable results-per-page (up to 100) to optimize data retrieval speed.
- Native support for structured exports to CSV, Excel, or JSON formats via the returned DataFrame object.
SKILL.md
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