chanlun

Name: chanlun
Availability: InStock
Author: 0xzknw

Detect fractals, strokes, and centers in OHLCV market data.

Updated Jun 30, 2026

Search Tags:#signals #technical analysis #trading #quantitative #market structure #chanlun

Ready to run

npx skills add https://github.com/0xZKnw/vibe-trading-tap --skill chanlun-0xzknw

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: chanlun
Source: https://github.com/0xZKnw/vibe-trading-tap/tree/main/agent/src/skills/chanlun
Command: npx skills add https://github.com/0xZKnw/vibe-trading-tap --skill chanlun-0xzknw

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This skill automates the complex and subjective process of Chanlun (Chan-Zhong-Shuo-Chan) technical analysis, removing human error in identifying market structures like fractals, strokes, and centers.

Core Features & Use Cases

Automated Structure Detection: Automatically identifies K-line fractals, strokes (BI), and centers (ZS) from raw OHLCV data.
Signal Generation: Detects high-probability buy and sell points (1st, 2nd, and 3rd buy/sell signals) based on divergence and trend exhaustion.
Use Case: A trader can use this to scan historical market data for specific buy/sell signals or to monitor real-time price action for trend reversals in crypto or stock markets.

Quick Start

Use the chanlun skill to analyze the provided market data and identify the latest buy or sell signals for the specified asset.

Frequently Asked Questions about chanlun

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

FAQPage Schema

How do I automate Chanlun technical analysis for market structure detection?▼

Automating Chanlun technical analysis involves processing raw OHLCV market data to deterministically identify fractals, strokes, and centers. This removes subjective human error from market structure detection and outputs deterministic buy and sell point signals for quantitative trading.

What are Chanlun buy and sell signals and how are they generated from OHLCV data?▼

Chanlun buy and sell signals are deterministic trading points generated by detecting trend exhaustion and divergence within market structures. The engine processes OHLCV data to identify the 1st, 2nd, and 3rd buy or sell signals based on fractal and stroke relationships.

Can I use pandas dataframes to scan historical market data for Chanlun trading signals?▼

Yes, you can use pandas dataframes containing historical OHLCV market data to scan for Chanlun trading signals. The engine processes the data to detect multi-period trends and identify specific buy or sell points for backtesting quantitative trading strategies.

Does this Chanlun analysis engine support real-time crypto and stock market data?▼

The Chanlun analysis engine processes OHLCV market data to monitor real-time price action for trend reversals in crypto or stock markets. It relies on the requests library to ingest market data for detecting fractals and generating live buy and sell signals.

What is the best way to identify market centers and fractals for quantitative trading?▼

The best way to identify market centers and fractals for quantitative trading is using an automated Chanlun engine. It mathematically processes OHLCV data to detect K-line fractals, strokes, and centers, providing deterministic signals without the subjectivity of manual charting.