quickdup

Detect duplicated code blocks across multi-language repositories using QuickDup tooling.

32|3|Updated Feb 12, 2026
One-click install
npx skills add https://github.com/asynkron/asynkron-skills --skill quickdup
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: quickdup
Source: https://github.com/asynkron/asynkron-skills/tree/main/skills/quickdup
Command: npx skills add https://github.com/asynkron/asynkron-skills --skill quickdup

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Duplicated code leads to maintenance pain and bugs. Quickdup helps teams detect and reduce code duplication across large codebases, supporting DRY and cleaner refactors.

Core Features & Use Cases

  • Detect identical or near-duplicate blocks across files or modules
  • Classify duplication patterns (structural, parameter bundle, argument unpacking) to guide refactoring
  • Generate actionable candidates with context for targeted cleanup and risk assessment

Quick Start

Run quickdup on a target path to surface top duplication candidates for review.

Frequently Asked Questions about quickdup

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

FAQPage Schema
How do I detect duplicated code patterns across a large multi-language codebase?

To detect duplicated code across a large multi-language codebase, scan the target path to surface similar blocks with two or more occurrences. This identifies identical and near-duplicate code patterns across files or modules for targeted cleanup.

What types of code clones can static analysis identify for refactoring?

Static analysis identifies structural, parameter bundle, and argument unpacking code clones. Classifying these duplication patterns guides specific refactoring strategies to reduce repetition and overall codebase size.

Can I adjust detection thresholds to ignore specific patterns during code cleanup?

Yes, you can adjust thresholds and configure ignore patterns during code cleanup. This filters static analysis results to ensure only actionable duplication candidates with relevant context are surfaced for review.

Does code duplication detection work for AI-assisted code review?

Code duplication detection outputs structured results specifically suitable for AI-assisted review. It generates actionable candidates with context to support targeted refactoring and risk assessment.

What is the best way to reduce codebase size by removing code clones?

The best way to reduce codebase size is running a duplication scan to classify code clones by type. This provides actionable refactoring candidates to eliminate structural repetition and support DRY principles.