A high-performance Python-based skill for retrieving comprehensive Chinese futures market data via Tushare Pro.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install tushare-future-data
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 tushare-future-data 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 Tushare Futures Data Connector?
This tool is a dedicated interface for the Tushare Pro platform, specifically designed to fetch futures data with high precision. Unlike generic connectors, it provides a transparent and predictable set of 14 core APIs covering market quotes, basic information, warehouse receipts, and settlement data. By integrating this into Openclaw Skills, developers and quantitative traders can build robust financial analysis agents that navigate complex futures markets with ease.
The skill emphasizes clarity and predictability, ensuring that users know exactly which endpoints are supported. This approach eliminates guesswork and trial-and-error, making it an essential component for any automated financial workflow requiring reliable futures data.
Tushare Futures Data Connector Use Cases
- Retrieving historical K-line data for futures contracts across daily, weekly, and monthly intervals.
- Accessing real-time intraday minute data for high-frequency trading simulations or market monitoring.
- Analyzing market sentiment through warehouse receipts and member holding rankings.
- Validating futures contract specifications, contract units, and trading calendars across multiple exchanges.
- Mapping internal and external futures contracts for cross-market arbitrage analysis.
How Tushare Futures Data Connector Works
- The user provides a valid Tushare Pro API token either via environment variables or direct parameters.
- The Openclaw Skills agent identifies the specific futures data requirement, such as daily quotes or holding rankings.
- The skill validates the request against its internal registry of 14 supported Tushare API endpoints.
- Input parameters like contract codes (ts_code) and date ranges are formatted to meet the strict Tushare API requirements.
- The skill executes the request using the Python Tushare client and processes the resulting Pandas DataFrame into a structured JSON response.
Tushare Futures Data Connector Setup
To use this connector within your Openclaw Skills environment, follow these steps:
- Obtain an API token from the Tushare Pro official website.
- Configure your environment variable:
export TUSHARE_TOKEN='your_api_token_here'
- Alternatively, pass the token directly in the JSON request payload.
- Ensure Python dependencies are installed:
pip install tushare pandas
Tushare Futures Data Connector Data Schema & Taxonomy
The skill returns a standardized JSON object for consistent integration with other Openclaw Skills.
| Field | Type | Description |
|---|---|---|
| success | boolean | Indicates if the data retrieval was successful |
| data | array | An array of objects containing the requested market data |
| msg | string | Status message or detailed error description |
| api | string | The specific Tushare API endpoint that was called |
Example data records include fields like open, high, low, close, settle, vol, and oi for market quote requests.
Tushare Futures Data Connector Advanced Features
- Support for granular historical minute data (1min, 5min, 15min, 30min, 60min) via the ft_mins endpoint.
- Real-time minute data capabilities through the rt_fut_min interface for live market tracking.
- Comprehensive exchange support covering CFFEX, SHFE, DCE, CZCE, INE, and GFEX.
- Explicit error handling for common issues like token expiration, permission limits, and invalid date formatting.
- Seamless integration with the broader ecosystem of Openclaw Skills for multi-agent financial research.
SKILL.md
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