A specialized AI skill for analyzing A-share stocks and ETFs using technical indicators to provide trend signals, scores, and real-time market snapshots.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install china-stock-analyzer
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 china-stock-analyzer 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 Stock-Analyzer?
Stock-Analyzer is a powerful integration for Openclaw Skills designed to simplify A-share market analysis. It leverages scripts to fetch market data from reliable providers like Sina and Tencent, calculating critical technical indicators such as MA, MACD, and RSI.
The skill provides a dual-mode workflow: it can deliver instantaneous intraday snapshots with level-2 bid/ask data or perform deep-dive trend analysis over custom timeframes. By synthesizing price action into actionable signals (Buy/Sell/Hold) and numerical scores, it helps developers and traders quickly assess market sentiment without manual charting.
Stock-Analyzer Use Cases
- Analyzing short-term trends for A-shares or ETFs like A500 or 159339.
- Determining if a specific stock is currently in a bullish, bearish, or sideways phase.
- Generating automated buy/sell/hold signals based on technical indicator crossovers.
- Getting real-time intraday quotes including 5-level market depth for immediate decision making.
- Scoring stock performance on a scale of 0-10 based on recent weekly and daily volatility.
How Stock-Analyzer Works
- Intent Parsing: The skill extracts the stock symbol or name and the desired timeframe from user input.
- Data Acquisition: It calls fetch.py to retrieve historical K-line data or real_time.py for live market snapshots via HTTP interfaces.
- Indicator Calculation: Technical metrics including Moving Averages (7, 14, 20, 60), MACD (12, 26, 9), and RSI14 are computed.
- Strategy Analysis: The analyze.py engine processes the data to determine the trend strength, reversal hints, and risk levels.
- Report Generation: The system outputs a structured natural language summary including the trend, signal, and a risk disclaimer.
Stock-Analyzer Setup
To use this within the Openclaw Skills environment, ensure you have Python 3.9+ installed along with the required dependencies:
pip install akshare pandas
You can verify the setup by running a test analysis on a stock like China Merchants Bank:
python scripts/strategy_analyzer.py 600036 --days 120
Stock-Analyzer Data Schema & Taxonomy
The skill organizes results into a structured format. The primary analysis output follows the taxonomy defined in scripts/analyze_result.md:
| Field | Description |
|---|---|
trend |
Bullish, Bearish, or Sideways |
signal |
Actionable advice: Buy, Sell, or Hold |
score |
0-10 rating of short-term strength |
weekly_change_pct |
Cumulative percentage change over the last 7 days |
risk_level |
Assessment of potential volatility or trend exhaustion |
bids/asks |
1-5 levels of market depth (Real-time mode only) |
Stock-Analyzer Advanced Features
- Multi-source data redundancy using Sina and Tencent providers to ensure high availability.
- Support for multiple adjustment methods including No-adjustment, Forward (QFQ), and Backward (HFQ).
- Integration-ready JSON outputs for automated trading bot hooks or multi-agent workflows.
- Detailed pattern recognition including Moving Average bias and spread analysis for momentum trading.
- Built-in prompt templates to convert raw technical data into professional trader-style reports.
SKILL.md
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