chanlun

Identify Chan Theory price structures and buy/sell signals from OHLCV data.

Updated Jul 29, 2026

Search Tags:#technical analysis #trading #algorithmic trading #market structure #chanlun #czsc

Ready to run

npx skills add https://github.com/santoosaraujo/vibe-trading-claude --skill chanlun-santoosaraujo

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: chanlun
Source: https://github.com/santoosaraujo/vibe-trading-claude/tree/main/.claude/skills/chanlun
Command: npx skills add https://github.com/santoosaraujo/vibe-trading-claude --skill chanlun-santoosaraujo

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires czsc, requests, pandas, and includes references (resource) components.

What problem does it solve?

This Skill automates the complex process of Chan Theory (缠论) technical analysis, removing the need for manual chart marking and subjective interpretation of price structures.

Core Features & Use Cases

Automated Structure Detection: Automatically identifies K-line patterns, strokes (Bi), and centers (Zhongshu) from raw market data.
Signal Generation: Detects precise buy and sell points (1st, 2nd, and 3rd categories) based on divergence and trend exhaustion.
Use Case: Traders can use this to scan large datasets of OHLCV market data to identify potential trend reversals or continuation points without manually drawing lines on charts.

Quick Start

Use the chanlun skill to analyze the provided OHLCV data for the specified asset and return all detected buy and sell signals.

Frequently Asked Questions about chanlun

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automate Chan Theory technical analysis for OHLCV market data?▼

Automated Chan Theory technical analysis processes raw OHLCV market data to identify K-line patterns, strokes, and centers. It removes manual chart marking by automatically detecting structural buy and sell signals across various financial assets.

What are the first, second, and third category buy and sell points in Chan Theory?▼

Chan Theory buy and sell points are specific trading signals generated by detecting divergence and trend exhaustion in price structures. The first, second, and third category points identify potential trend reversals or continuation points based on automated pattern classification.

Can I use the czsc library to scan large datasets for crypto and stock structures?▼

The czsc library supports multi-period analysis and pattern classification for various financial markets including stocks and crypto. You can scan large datasets of OHLCV market data to identify trading signals without manually drawing lines on charts.

How do I detect Zhongshu centers and Bi strokes from raw market data?▼

Detecting Zhongshu centers and Bi strokes requires processing raw OHLCV data through an automated technical analysis engine. The system identifies these price structures to evaluate market trends and generate precise divergence-based trading signals.

Does automated Chan Theory analysis support multi-period pattern classification?▼

Automated Chan Theory analysis supports multi-period pattern classification to evaluate market structure across different timeframes. This allows traders to process OHLCV data and detect structural buy and sell signals across various financial markets simultaneously.

What are the limitations of using automated Chan Theory for trading signals?▼

Automated Chan Theory relies entirely on processing OHLCV data into structured buy and sell signals based on historical price structures. It does not account for fundamental market factors and requires prerequisite data formatting to accurately detect strokes, centers, and divergence.