refactor

Analyze codebases for code smells and technical debt using Python scripts.

Updated Feb 5, 2026
One-click install
npx skills add https://github.com/flybirdxx/RunningHub --skill refactor-flybirdxx
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: refactor
Source: https://github.com/flybirdxx/RunningHub/tree/main/.gemini/skills/refactor
Command: npx skills add https://github.com/flybirdxx/RunningHub --skill refactor-flybirdxx

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill provides an automated way to identify code smells and technical debt, simplifying the refactoring process and enhancing code quality.

Core Features & Use Cases

  • Code Smell Detection: Automatically identify common code quality issues such as duplicated code, long methods, and feature envy.
  • Technical Debt Analysis: Assess and report on technical debt across a codebase.
  • Workflow Automation: Automate the entire process from detecting code smells to synthesizing actionable work items.
  • Use Case: Use this Skill to analyze a codebase and generate a report on potential refactoring opportunities, helping developers prioritize and streamline their refactoring efforts.

Quick Start

Run the refactor skill on your codebase using the following command: python3 ${extensionPath}/scripts/refactor.py --step 1 --total-steps 5 --n 10

Frequently Asked Questions about refactor

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

FAQPage Schema
How do I identify code smells and technical debt in my codebase?

To identify code smells and technical debt, you can automate code refactoring analysis using Python scripts to detect duplicated code, long methods, and feature envy. This process assesses your codebase and generates a report of potential refactoring opportunities.

How do I automate code refactoring analysis to generate actionable work items?

You automate code refactoring analysis by running a workflow orchestration script that detects code smells and synthesizes actionable work items. Executing the Python script processes your codebase in steps to streamline refactoring efforts.

What is the best way to assess technical debt across a Python codebase?

The best way to assess technical debt is to run an automated analysis script that evaluates your codebase for code quality issues. This generates a detailed report highlighting technical debt and prioritizing refactoring opportunities.

Can I use this code analysis workflow for large codebases with multiple steps?

Yes, you can analyze large codebases by configuring the script execution with specific step and total-step parameters. This allows the analysis to process the codebase systematically across defined stages to manage technical debt.

What types of code quality issues can automated refactoring analysis detect?

Automated refactoring analysis detects common code quality issues such as duplicated code, long methods, and feature envy. Identifying these code smells helps prioritize technical debt remediation and enhance maintainability.