A sophisticated multi-agent framework for deep A-share market research, industry chain analysis, and automated investment reporting.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install astock-multiagent-research
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 astock-multiagent-research 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 A-Share Multi-Agent Research Framework?
The A-Share Multi-Agent Research Framework is a comprehensive system designed to automate the lifecycle of stock market analysis. By deploying a swarm of specialized agents—including fundamental, news, sentiment, and technical analysts—it provides a 360-degree view of any listed company. This skill is a core component for investors looking to leverage high-fidelity data and objective AI perspectives available through Openclaw Skills.
The system doesn't just aggregate data; it fosters a 'perspective collision' by assigning specific agents to argue bullish and bearish cases. This ensures that the final investment reports are balanced, fact-checked, and grounded in real-time data from sources like akshare and yfinance.
A-Share Multi-Agent Research Framework Use Cases
- Conduct deep-dive financial and technical analysis for specific A-share ticker codes.
- Map out complex industry chains to identify value drivers in sectors like AI computing or commercial aerospace.
- Perform institutional-grade risk assessments covering liquidity, policy, and financial health.
- Generate interactive HTML dashboards for visualizing stock performance and valuation metrics.
How A-Share Multi-Agent Research Framework Works
- Multi-dimensional data collection is triggered via four parallel sub-agents handling fundamentals, news, sentiment, and technicals.
- Perspective collision occurs as bullish and bearish researchers debate growth potential against valuation bubbles.
- A risk manager agent synthesizes industry, financial, and policy risks into a unified assessment.
- The fact-checker agent performs a secondary verification of all key data points and claims.
- Reports are generated following a standardized template including valuation percentiles and institutional ratings.
- The final output is rendered into an interactive HTML Dashboard and deployed for easy access.
A-Share Multi-Agent Research Framework Setup
To initialize the environment for this skill on Openclaw Skills, ensure you have the necessary data fetching libraries installed:
pip install akshare yfinance
You can then fetch data for a specific stock (e.g., 300442) using the provided script:
python scripts/fetch_stock_data.py 300442
A-Share Multi-Agent Research Framework Data Schema & Taxonomy
The skill organizes research data into a structured taxonomy for clarity and comparison:
| Data Layer | Metadata / Metrics Included |
|---|---|
| Research Summary | Company positioning, industry status, and current valuation status. |
| Financial Analysis | Revenue, Net Profit, Gross Margin, and ROE with YoY growth comparisons. |
| Valuation Metrics | PE, PB, and PS historical percentiles. |
| Institutional Data | Rating distribution, target price ranges, and fund holding changes. |
| Risk Profile | Qualitative and quantitative assessment of industry and policy risks. |
A-Share Multi-Agent Research Framework Advanced Features
- Multi-agent session spawning for parallel execution of analytical tasks.
- Automated industry chain decomposition using pre-defined reference frameworks.
- Integration with yfinance for cross-market analysis of US and HK stocks alongside A-shares.
- Interactive HTML dashboard deployment providing a professional-grade visualization of research findings.
SKILL.md
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