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DaichiHoshina
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techdebt

Scan codebases for duplication and DRY violations and generate refactor proposals.

Updated Aug 23, 2026
Search Tags:#refactor#code-quality#duplication#static-analysis#code-smell#techdebt#dry-violation
One-click install
npx skills add https://github.com/DaichiHoshina/ai-tools --skill techdebt-daichihoshina
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: techdebt
Source: https://github.com/DaichiHoshina/ai-tools/tree/main/claude-code/skills/techdebt
Command: npx skills add https://github.com/DaichiHoshina/ai-tools --skill techdebt-daichihoshina

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill automatically detects technical debt such as duplicated code and DRY-violations, and suggests targeted refactors to improve maintainability and quality.

Core Features & Use Cases

  • Automated debt detection: scans codebases for duplication, magic numbers, and repeated validation patterns.
  • Refactor proposals: provides concrete, language-agnostic refactoring suggestions with before/after examples.
  • Phase-based workflow: supports scanning, filtering, similarity checks, and generation of actionable proposals.

Quick Start

Run a full techdebt scan on your repository to surface actionable refactor proposals.

Frequently Asked Questions about techdebt

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

FAQPage Schema
How do I detect DRY violations and code duplication in a multi-language repository?▼

Detecting DRY violations involves phase-based scanning and similarity analysis to identify duplicated code blocks, magic numbers, and repeated validation patterns across multi-language codebases.

What is the best way to generate actionable refactor proposals from static analysis?▼

The best way to generate refactor proposals is running a full technical debt scan that identifies code smells and outputs concrete, language-agnostic refactoring suggestions with before and after examples.

Can I use automated techdebt detection for pre-merge checks in Go and TypeScript projects?▼

Yes, automated technical debt detection supports Go and TypeScript projects for pre-merge checks, applying phase-based scanning and exclusion filtering to surface duplication before integration.

Does code smell detection work with Rust and Python codebases?▼

Code smell detection works with Rust and Python codebases by applying duplicate detection and similarity analysis to identify DRY violations and generate targeted refactoring guidance.

How do I exclude specific files or directories when scanning for technical debt?▼

To exclude files or directories during technical debt scanning, apply exclusion filtering to narrow the phase-based scan, reducing noise and focusing duplicate detection on relevant code paths.

What are the limitations of automated duplication detection for refactor planning?▼

A limitation of automated duplication detection is that generated refactor proposals are language-agnostic guidance requiring manual implementation and validation during refactor planning.

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