A comprehensive quantitative finance tool for accessing Chinese A-share market data, financial statements, and sector insights using the AkShare library.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install akshare-stock-tmp
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 akshare-stock-tmp 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 akshare-stock?
The akshare-stock skill is a powerful integration for AI agents designed to navigate the complexities of the Chinese equity market. Built upon the robust AkShare library, this skill enables agents to retrieve a vast array of financial data points, ranging from real-time price action to deep fundamental analysis. It serves as a bridge between raw financial datasets and actionable intelligence.
By implementing this skill, developers can equip their agents to answer sophisticated queries regarding market trends, individual stock performance, and institutional movements. Whether you are building an automated researcher or a quantitative trading assistant, akshare-stock provides the necessary data hooks to power high-fidelity financial analysis within the Openclaw Skills ecosystem.
akshare-stock Use Cases
- Real-time monitoring of A-share price fluctuations and market spot data.
- Comprehensive financial statement analysis and key performance indicator (KPI) tracking for listed companies.
- Sector and industry-level rotation analysis to identify trending market themes.
- Tracking institutional activity through Dragon-Tiger lists (LHB) and corporate surveys.
- Historical backtesting support by fetching daily, weekly, or monthly K-line data with price adjustments.
How akshare-stock Works
- The AI agent receives a financial query related to the Chinese A-share market.
- The agent invokes the akshare-stock skill to interface with the AkShare Python library.
- The skill executes specific API calls to fetch data from various financial sources (e.g., East Money, THS).
- Retreived data is structured into a usable format for the LLM to process.
- If a primary interface fails, the system can utilize fallback mechanisms like Baostock to ensure data continuity.
akshare-stock Setup
To begin using akshare-stock, ensure your environment has the necessary dependencies installed. You can install the primary library via pip:
pip install akshare
If you require the lightweight fallback option, you may also install Baostock:
pip install baostock
akshare-stock Data Schema & Taxonomy
The skill organizes data into several logical domains to ensure high retrieval accuracy:
| Data Category | Key Indicators | Sources/Methods |
|---|---|---|
| Market Spot | Price, Change %, Volume | stock_zh_a_spot_em |
| Historical Data | Open, High, Low, Close (OHLC) | stock_zh_a_hist |
| Financials | Balance Sheets, Ratios, EPS | stock_financial_analysis_indicator |
| Capital Flow | Large Order Inflow, Net Flow | stock_individual_fund_flow |
| IPO Info | Subscription dates, listing status | stock_new_ipo_em |
All data is processed as structured DataFrames or Lists before being interpreted by the agent.
akshare-stock Advanced Features
- Multi-period K-line support including daily, weekly, and monthly intervals with forward/backward adjustment options.
- Institutional insight tools including specialized tracking for agency surveys and Dragon-Tiger list details.
- Built-in redundancy through the Baostock integration for high-availability data sourcing.
- Support for Margin Trading and Securities Lending data analysis (SSE/SZSE).
- Sector-specific drill-downs allowing agents to map individual stocks to their respective industry or concept boards.
SKILL.md
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