An advanced A-share quantitative trading assistant providing real-time data, technical indicators, and automated decision support.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install quant-trading-assistant
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install quant-trading-assistant using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Quant Trading Assistant is a specialized tool designed for the Chinese A-share market, integrating real-time price feeds from Tencent and Sina APIs with sophisticated technical analysis. It moves beyond simple data display by providing actionable trading signals, market sentiment tracking, and risk assessment.
This Openclaw Skills integration empowers developers and traders to automate stock screening based on fundamental growth metrics and technical triggers. It features deep analysis of indicators like MACD, KDJ, and Bollinger Bands, alongside a unique sentiment engine to identify market cycles such as high-tide or retreat phases.
To use this tool within the Openclaw Skills framework, ensure your environment supports Python. You can execute commands directly via the CLI:
# Analyze a specific stock (e.g., Kweichow Moutai)
python quant_trading_assistant.py analyze sh600519
# Perform a quantitative market screen
python quant_trading_assistant.py screen
# Check current market sentiment
python quant_trading_assistant.py sentiment
The skill organizes data into a structured format for easy integration and display. Key data points include:
| Data Point | Description | Example |
|---|---|---|
| Real-time Quote | Price, change pct, volume, PE, PB | {price: 1800, change: 1.5} |
| Technicals | MA(5,10,20,60), KDJ, MACD, BOLL | {ma5: 1750, k: 45} |
| Market Sentiment | Phase, score, and turnover | {phase: 'Launch', score: 85} |
| Risk Check | Safety level and specific risk points | {risk_level: 'Safe'} |
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