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p3-g0b-verify

Verify trading strategy code for look-ahead bias and position sizing.

Updated Aug 27, 2026
Search Tags:#code review#python#risk management#backtesting#strategy verification#quant development
One-click install
npx skills add https://github.com/mentalcrash/mc-coin-bot --skill p3-g0b-verify
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: p3-g0b-verify
Source: https://github.com/mentalcrash/mc-coin-bot/tree/main/.claude/skills/p3-g0b-verify
Command: npx skills add https://github.com/mentalcrash/mc-coin-bot --skill p3-g0b-verify

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires Bash, Read, Grep, Glob, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill acts as a critical senior quant developer to rigorously verify the correctness and safety of trading strategy code before backtesting, preventing costly errors and ensuring financial integrity.

Core Features & Use Cases

  • Automated Code Scanning: Detects common critical flaws like look-ahead bias, data leakage, and incorrect position sizing using predefined patterns.
  • Adherence to Project Rules: Ensures strategies follow strict coding standards (e.g., Shift(1) Rule, Vectorization, Statelessness).
  • Use Case: After implementing a new trading strategy, use this Skill to perform a thorough code review, identifying potential bugs and ensuring it meets the project's high standards for live trading.

Quick Start

Verify the strategy code in the 'src/strategy/my_new_strategy' directory.

Frequently Asked Questions about p3-g0b-verify

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

FAQPage Schema
How do I check my Python trading strategy for look-ahead bias before backtesting?▼

To check trading strategy code for look-ahead bias before backtesting, perform a rigorous code verification scanning for data leakage and incorrect shift usage. This ensures your Python implementation adheres to strict statelessness and vectorization standards.

What is the Shift(1) rule in quantitative strategy code verification?▼

The Shift(1) rule in quantitative strategy verification ensures strategies only use previously available data for current calculations, preventing future data leakage. Automated code scanning checks your project's adherence to this strict standard for financial integrity.

How do I verify position sizing logic in my backtesting code?▼

To verify position sizing logic in backtesting code, run a critical code review that rigorously checks implementation correctness against predefined patterns. This identifies potential bugs and ensures your strategy meets high standards for live trading readiness.

Does code review for quant development require vectorized Python implementations?▼

Code review for quant development requires vectorized Python implementations to meet strict project coding standards. Verifying vectorization ensures your trading strategy operates efficiently and correctly during backtesting and live trading execution.

What's the best way to automate risk management checks for trading strategies?▼

The best way to automate risk management checks for trading strategies is performing an automated code scan that detects critical flaws like data leakage using predefined patterns. This acts as a senior quant developer to ensure financial integrity.

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