wadituwadituOfficial·3 Agent Skills Included

czsc

Chan theory quantitative trading analysis, signals, and backtesting toolkit

Automates Chan theory technical analysis by detecting fractals, strokes, and pivots directly from K-line data. Generates over 220 trading signals, combines them into events and positions, and runs multi-timeframe backtests without manual chart reading. Connects to Tushare, CCXT, and TQ data sources and outputs interactive HTML reports to speed up strategy research.
npx skills add waditu/czsc --all -g -y
Available:

Tells the AI agent how the Rust-Python hybrid codebase is organized, which commands to run for testing and building, and the strict rules for keeping Rust and Python behavior identical when developing signals or strategies.

All Skills in This Repository (3)

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Frequently Asked Questions

FAQPage Schema
How to install czsc?

Run `npx skills add waditu/czsc --all -g -y` in your terminal to install all skills in this suite globally.

What is czsc used for?

It is a quantitative trading library based on Chan theory that automatically identifies fractals, strokes, and pivots, then generates trading signals and runs backtests.

How do I write a new czsc signal function?

Use the czsc-write-signal-function skill, which guides your AI agent to draft the Rust function, register it with the signal macro, and verify it triggers events correctly.

Which data sources does czsc support?

It connects to Tushare for A-share data, TQ for futures, CCXT for crypto exchanges, and local cached research data through a unified interface.

Do I need to know Rust to use czsc?

No. Everyday analysis runs through simple Python APIs, while the Rust core works behind the scenes for speed.

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