pine-script

Translate Python trading strategies into native TradingView, TDX, and MetaTrader 5 code.

Updated Jun 30, 2026
One-click install
npx skills add https://github.com/0xZKnw/vibe-trading-tap --skill pine-script-0xzknw
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: pine-script
Source: https://github.com/0xZKnw/vibe-trading-tap/tree/main/agent/src/skills/pine-script
Command: npx skills add https://github.com/0xZKnw/vibe-trading-tap --skill pine-script-0xzknw

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill solves the fragmentation of trading platform ecosystems by enabling users to translate a single Vibe-Trading strategy into native code for multiple major trading platforms simultaneously.

Core Features & Use Cases

  • Multi-Platform Export: Automatically generates code for TradingView (Pine Script v6), Chinese equity platforms (TDX/TongDaXin), and MetaTrader 5 (MQL5).
  • Logic Mapping: Provides a robust translation layer between Python-based data science logic and platform-specific indicator syntax.
  • Use Case: A quantitative researcher develops a signal engine in Python and uses this skill to instantly deploy the strategy as a custom indicator on TradingView for visual backtesting and on MT5 for automated execution.

Quick Start

Use the pine-script skill to translate the current strategy logic into indicator code for all supported trading platforms.

Frequently Asked Questions about pine-script

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

FAQPage Schema
How do I translate a Python trading strategy into Pine Script?

To translate a Python trading strategy into Pine Script, this skill maps your quantitative signal engine logic into native TradingView indicator code, supporting complex technical analysis like moving averages, RSI, and MACD across diverse platform syntaxes.

Can I convert Python signal logic into MQL5 for MetaTrader 5?

Yes, you can convert Python signal logic into MQL5 for MetaTrader 5. The skill translates your unified strategy definition into native MQL5 code, enabling automated execution directly from your Python-based quantitative models.

How do I export backtesting strategies to TDX?

You can export backtesting strategies to TDX by using the skill's multi-platform export feature. It automatically generates native indicator and strategy code for Chinese equity platforms like TongDaXin from your unified strategy definition.

Does this tool support translating custom technical indicators across platforms?

Yes, it supports translating custom technical indicators across platforms. The skill provides a robust translation layer between Python-based data science logic and platform-specific syntaxes for TradingView, TDX, and MetaTrader 5.

What is the best way to deploy a single quantitative strategy on multiple trading platforms?

The best way to deploy a single quantitative strategy on multiple platforms is to define it once in Python and use this skill to instantly generate platform-specific artifacts for TradingView, TDX, and MT5 simultaneously.

Why use a translation layer for cross-platform strategy deployment?

A translation layer is used for cross-platform strategy deployment to solve trading platform ecosystem fragmentation. It bridges Python data science logic with platform-specific indicator syntax, allowing simultaneous visual backtesting and automated execution.