An automated AI quantitative stock selection system that analyzes A-share markets using a multi-dimensional scoring model to generate daily investment reports.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install quant-stock
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 quant-stock 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 Quant Stock Picker?
Quant Stock Picker is a comprehensive Openclaw Skills module designed for systematic A-share market analysis. It utilizes a sophisticated scoring engine across six core dimensions, including technical indicators, market sentiment, and news sentiment. By automating the evaluation of sectors like semiconductors, new energy, and AI, this tool provides developers and traders with a data-driven approach to stock selection. This Openclaw Skills implementation bridges the gap between raw financial data and actionable investment intelligence, ensuring consistent post-market analysis without manual overhead.
Quant Stock Picker Use Cases
- Automated daily post-market stock screening for A-share markets.
- High-frequency sector scanning across AI, robotics, semiconductors, and green energy.
- Generation of professional-grade investment reports for distribution via Feishu or local files.
- Systematic risk assessment through negative-weighted sentiment and market trend analysis.
How Quant Stock Picker Works
- The system initializes a local stock pool containing target codes, names, and industry classifications.
- A main analysis engine evaluates every stock in the pool against six scoring modules: Technicals, Sentiment, Index Trends, Industry Themes, News, and Sector Optimization.
- Scoring logic applies weights, such as +3 for MACD Golden Crosses or -10 for major negative news, to calculate a total score for each asset.
- The tool identifies the TOP 3 stocks and secondary candidates (ranks 4-10) based on cumulative performance.
- Reports are automatically formatted and delivered via configured Feishu webhooks or local text exports.
Quant Stock Picker Setup
Install the required dependencies using pip:
pip install pandas requests
Initialize your local stock pool database:
python scripts/init_pool.py
Configure your reporting credentials in feishu_config.json and execute the daily analysis:
python scripts/main.py
To automate the workflow with Openclaw Skills, install the daily cron job (set for 15:30 daily):
bash scripts/install_cron.sh
Quant Stock Picker Data Schema & Taxonomy
The skill manages its state and logic through the following data structures:
| Component | Format | Description |
|---|---|---|
| stock_pool.csv | CSV | Primary database of stock codes, industry tags, and names |
| feishu_config.json | JSON | API credentials for Lark/Feishu integration (app_id, app_secret) |
| daily_report.txt | Text | Output file generated after each analysis run |
| scoring_rules | Markdown | Defined in RULES.md, containing positive and negative weighting logic |
Quant Stock Picker Advanced Features
- Multi-agent ready modular architecture for news sentiment and industry updates.
- Automated scheduling via integrated Bash cron scripts for hands-off operation.
- Real-time news sentiment analysis with specialized weighting for major market events.
- High-performance data processing using pandas for rapid large-pool evaluation.
- Customizable scoring hooks to adjust strategy weights according to market volatility.
SKILL.md
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