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pine-script

Translate Python trading strategies into Pine Script, TDX, and MQL5 code.

Updated Jul 29, 2026
Search Tags:#strategy#trading#backtest#mql5#tdx#pine-script#quant
One-click install
npx skills add https://github.com/santoosaraujo/vibe-trading-claude --skill pine-script-santoosaraujo
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pine-script
Source: https://github.com/santoosaraujo/vibe-trading-claude/tree/main/.claude/skills/pine-script
Command: npx skills add https://github.com/santoosaraujo/vibe-trading-claude --skill pine-script-santoosaraujo

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill solves the fragmentation of trading platform ecosystems by automating the translation of Python-based backtest strategies into native code for TradingView, TDX, and MT5 simultaneously.

Core Features & Use Cases

  • Multi-Platform Export: Generates Pine Script v6, TDX formulas, and MQL5 code from a single source of truth.
  • Logic Mapping: Automatically converts pandas/numpy strategy logic into platform-specific syntax like ta.sma or REF().
  • Use Case: A quantitative analyst develops a signal engine in Python and uses this skill to instantly deploy the same logic across their TradingView charts, local Chinese brokerage software, and MetaTrader 5 terminal.

Quick Start

Use the pine-script skill to translate the current strategy logic into code for TradingView, TDX, and MT5.

Frequently Asked Questions about pine-script

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

FAQPage Schema
How do I convert a Python trading strategy into Pine Script, TDX, and MQL5?▼

You can convert Python-based quantitative trading strategies by automatically translating pandas and numpy logic into native Pine Script v6, TDX formulas, and MQL5 code simultaneously from a single source.

Does this translation tool support automated syntax mapping for technical indicators across multiple platforms?▼

Yes, automated syntax mapping ensures semantic consistency by converting standard Python logic into platform-specific syntax like ta.sma for TradingView and REF() for TDX formulas.

Can I use my Python backtest signal engine to deploy strategies directly to TradingView and MetaTrader 5?▼

Yes, quantitative analysts can take a Python signal engine and instantly deploy the exact same entry and exit logic across TradingView charts and MetaTrader 5 terminals.

What is the best way to maintain semantic consistency of entry and exit logic across different trading software?▼

Using an automated code translation skill ensures semantic consistency of technical indicators and entry/exit logic by mapping a single Python strategy into native platform code.

Do I need to rewrite my numpy and pandas strategy logic manually for each trading platform?▼

No, you do not need to manually rewrite logic. The skill automatically maps numpy and pandas backtest logic into the specific syntax required for TradingView, TDX, and MT5.

Why use a cross-platform strategy export tool instead of coding Pine Script and MQL5 separately?▼

Cross-platform strategy export solves trading platform fragmentation by generating Pine Script, TDX, and MQL5 code simultaneously, preventing manual coding errors and logic divergence.

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