Access comprehensive Chinese financial market data, including A-shares, indices, mutual funds, and macro indicators via AKShare.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ashare
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 ashare 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 ashare?
The ashare skill provides AI agents with direct access to the Chinese financial ecosystem through the AKShare library. It allows for high-precision querying of market breadth, real-time stock quotes, historical price data, and macroeconomic indicators. By integrating this into Openclaw Skills, developers can move beyond unreliable web scraping and utilize structured, programmatic data for financial analysis and reporting.
This skill is optimized for performance and accuracy, ensuring that data like net asset values (NAV) for mutual funds and macro-economic calendars are retrieved in a format ready for immediate processing by AI models. It acts as a bridge between complex financial APIs and the conversational capabilities of coding agents.
ashare Use Cases
- Querying real-time price quotes and daily changes for A-share stocks.
- Retrieving historical K-line data for indices and individual securities to perform trend analysis.
- Monitoring open-end mutual fund daily NAV snapshots and historical returns.
- Accessing macro-economic data series such as Chinese CPI, PMI, and RMB exchange rates.
- Generating automated financial news flashes and market overviews for daily briefings.
How ashare Works
- The AI agent identifies a financial query and converts any relative dates into the absolute YYYYMMDD format.
- The request is mapped to a specific subcommand supported by the internal query script.
- The agent executes the bundled Python script using the Openclaw Skills execution environment.
- The AKShare library fetches the requested data and returns a structured JSON envelope.
- The agent parses the JSON and generates a concise summary in Chinese, highlighting the most relevant market values.
ashare Setup
To enable this skill, ensure that Python is installed in your environment. The skill uses a bundled script to interface with the AKShare library. Use the following command structure within your Openclaw Skills workflow:
# Install the required dependency if missing
pip install akshare
# Execute a market query
python "{baseDir}/scripts/query_akshare.py" market-overview
ashare Data Schema & Taxonomy
Every successful request returns a JSON object designed for easy parsing by AI agents. The schema includes:
| Property | Description |
|---|---|
ok |
Indicates if the query was successful (boolean) |
dataset |
The specific market dataset accessed |
resolved |
The symbol or name resolved for the query |
columns |
An array of data headers |
rows |
The actual data points returned from the market |
as_of |
The timestamp of the data retrieval |
ashare Advanced Features
- Intelligent symbol resolution that handles ambiguous stock or fund names by surfacing candidates.
- Support for adjusted historical data (none, qfq, hfq) to ensure accuracy in technical analysis.
- Granular period selection for historical queries, ranging from daily to monthly intervals.
- Automated error handling that provides specific diagnostic types like missing_dependency or ambiguous_symbol within Openclaw Skills.
- Integration with Eastmoney for comprehensive company and security profiling.
SKILL.md
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