chanlun-analyzer

What This Skill Does

The chanlun-analyzer is a robust, production-grade technical analysis engine designed to implement the complex principles of Chan Theory (缠论) within the OpenClaw ecosystem. Utilizing a rigorous 6-layer processing architecture derived from the czsc (waditu/czsc) algorithmic framework, this skill transforms raw financial data into structured market insights. It performs sophisticated tasks including candlestick inclusion handling, fractal identification, pen generation, center (zhongshu) construction, and divergence-based momentum analysis. By automating the identification of buy points (2-buy and 3-buy) and sell signals, it provides traders with a deterministic, rule-based approach to market structure analysis, eliminating the subjective interpretation often associated with manual charting.

Installation

To integrate this analysis engine into your OpenClaw environment, use the following terminal command:

clawhub install openclaw/skills/skills/antfraud/chanlun-analyzer

This skill is built as a zero-dependency Python package requiring Python 3.8 or higher. It utilizes standard library modules exclusively to ensure high performance and stability without requiring heavy package management for common utility functions.

Use Cases

1. Automated Trading Signals: Integrate the analyzer into your pipeline to trigger buy or sell alerts based on confirmed 2-buy or 3-buy signals identified via MACD divergence.
2. Historical Backtesting: Analyze historical price data for specific tickers (e.g., SZ002815) over defined periods to observe how the 6-layer structure performs against real market movement.
3. Trend Analysis: Use the pen and center extraction features to visualize the current market trend without needing third-party charting software.

Example Prompts

1. "缠论分析，分析股票 sz002815 过去250个交易日的走势，重点查看是否有3买机会。"
2. "笔和中枢是什么情况？请帮我识别 sh600540 当前最新的缠论结构。"
3. "缠论结构分析：对比腾讯接口数据，输出 sz000001 的所有买点信号并以JSON格式返回。"

Tips & Limitations

• Tips: For the most accurate results, ensure your symbol string includes the exchange prefix (e.g., 'sz' or 'sh'). The engine relies on Tencent K-line data with automatic forward-adjustment (qfq), providing consistency in analysis.
• Limitations: The engine relies on standard MACD area divergence calculations for momentum. While this is effective, extreme market volatility may result in fragmented center structures. Always verify signals against broader market conditions. The current version does not support real-time tick-by-tick updates; it is optimized for daily K-line analysis.