vnpy-export

Translate Vibe-Trading backtest strategies into executable vnpy CtaTemplate Python classes.

Updated Jun 30, 2026
One-click install
npx skills add https://github.com/20YN04/vibe-trading-macos --skill vnpy-export-20yn04
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: vnpy-export
Source: https://github.com/20YN04/vibe-trading-macos/tree/main/agent/src/skills/vnpy-export
Command: npx skills add https://github.com/20YN04/vibe-trading-macos --skill vnpy-export-20yn04

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This skill bridges the gap between Vibe-Trading's research environment and the vnpy quant framework, allowing users to seamlessly transition from strategy backtesting to live trading or professional-grade backtesting.

Core Features & Use Cases

  • Automated Translation: Converts Vibe-Trading signal logic into a fully functional vnpy CtaTemplate Python class.
  • Multi-Asset Support: Handles A-share stocks, futures, and crypto with appropriate parameter and position conventions.
  • Use Case: A user develops a profitable strategy in Vibe-Trading and wants to deploy it on their local vnpy instance for live trading; this skill generates the necessary boilerplate code and indicator mappings instantly.

Quick Start

Use the vnpy-export skill to translate the current strategy into a runnable CtaTemplate file for the vnpy CTA Strategy App.

Frequently Asked Questions about vnpy-export

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

FAQPage Schema
How do I convert a Vibe-Trading backtest strategy into a vnpy CtaTemplate class?

To convert a Vibe-Trading backtest strategy into a vnpy CtaTemplate class, use automated translation to map signal logic and ArrayManager indicators into executable Python code for live trading.

Can I deploy CTA strategies for A-share equities, futures, and crypto using vnpy?

Yes, you can deploy CTA strategies for A-share equities, futures, and crypto using vnpy by mapping custom trading signals to appropriate parameter and position conventions for each asset class.

What's the best way to translate custom trading signals into the vnpy ecosystem?

The best way to translate custom trading signals into the vnpy ecosystem is through automated code generation that adheres to CtaTemplate structures and maps indicators via ArrayManager.

How does automated code generation map signal logic to ArrayManager indicators?

Automated code generation maps signal logic to ArrayManager indicators by translating Vibe-Trading backtest rules directly into functional Python class methods within the vnpy CtaTemplate framework.

Do I need to manually write boilerplate code when transitioning strategies to vnpy?

No, you do not need to manually write boilerplate code when transitioning strategies to vnpy because the translation process automatically generates the necessary boilerplate and indicator mappings instantly.

Does vnpy-export support professional-grade backtesting after translating Vibe-Trading signals?

Yes, vnpy-export supports professional-grade backtesting after translating Vibe-Trading signals by generating fully runnable CtaTemplate files compatible with the vnpy CTA Strategy App.