rubberduck-mirror-pro

Compare code implementations for behavioral equivalence using RubberDuck semantic analysis.

Updated Apr 7, 2026
One-click install
npx skills add https://github.com/faizanarshad/rubber_duck --skill rubberduck-mirror-pro
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: rubberduck-mirror-pro
Source: https://github.com/faizanarshad/rubber_duck/tree/main/.cursor/skills/rubberduck-mirror-pro
Command: npx skills add https://github.com/faizanarshad/rubber_duck --skill rubberduck-mirror-pro

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill identifies and verifies safe replacements or refactors of code without altering its behavior, reducing the risk of introducing bugs.

Core Features & Use Cases

  • Equivalence Checking: Compare code implementations for behavioral consistency.
  • Code Replacement Safety: Validate if a replacement code is safe and maintains the original functionality.
  • Refactoring Checks: Safely refactor code and ensure the changes don't affect behavior.
  • Use Case: Use the rubberduck-mirror-pro skill to check if a new function replaces an old one while preserving all observable behaviors.

Quick Start

Compare the before and after code snippets using rubberduck-mirror-pro.

Frequently Asked Questions about rubberduck-mirror-pro

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

FAQPage Schema
How do I verify behavioral equivalence when refactoring code?

To verify behavioral equivalence during code refactoring, compare the before and after code snippets using semantic intelligence to ensure the replacement maintains the original functionality without introducing bugs.

What is behavioral equivalence checking in code reviews?

Behavioral equivalence checking in code reviews is the process of comparing code implementations using full semantic analysis to validate that changes or replacements preserve all observable behaviors and maintain code safety.

How do I ensure safe code replacement for AI-patch implementations?

To ensure safe code replacement for AI-patch implementations, apply semantic intelligence to compare the new function against the old one, establishing specific contracts to verify that the automated system maintains the original behavior.

Can I use semantic analysis to validate code replacement safety?

Yes, you can use semantic analysis to validate code replacement safety by checking for behavioral consistency between implementations, requiring specific contracts to establish accuracy and confirm that the refactor does not alter behavior.

When do I need behavioral validation for code refactoring?

You need behavioral validation for code refactoring when replacing an old function with a new one, especially in automated systems like code generators, to reduce the risk of introducing bugs and ensure the changes do not affect behavior.

What are the limitations of checking code equivalence with semantic intelligence?

A limitation of checking code equivalence with semantic intelligence is that it requires full semantic analysis for accuracy and specific contracts to establish equivalence, meaning vague replacements without clear behavioral definitions may not validate correctly.