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    About

    Assess, quantify, and prioritize technical debt using code analysis, metrics, and impact analysis. Use when planning refactoring, evaluating codebases, or making architectural decisions.

    SKILL.md

    Technical Debt Assessment

    Table of Contents

    • Overview
    • When to Use
    • Quick Start
    • Reference Guides
    • Best Practices

    Overview

    Systematically identify, measure, and manage technical debt to make informed decisions about code quality investments.

    When to Use

    • Legacy code evaluation
    • Refactoring prioritization
    • Sprint planning
    • Code quality initiatives
    • Acquisition due diligence
    • Architectural decisions

    Quick Start

    Minimal working example:

    interface DebtItem {
      id: string;
      title: string;
      description: string;
      category: "code" | "architecture" | "test" | "documentation" | "security";
      severity: "low" | "medium" | "high" | "critical";
      effort: number; // hours
      impact: number; // 1-10 scale
      interest: number; // cost per sprint if not fixed
    }
    
    class TechnicalDebtAssessment {
      private items: DebtItem[] = [];
    
      addDebtItem(item: DebtItem): void {
        this.items.push(item);
      }
    
      calculatePriority(item: DebtItem): number {
        const severityWeight = {
          low: 1,
          medium: 2,
          high: 3,
          critical: 4,
        };
    // ... (see reference guides for full implementation)
    

    Reference Guides

    Detailed implementations in the references/ directory:

    Guide Contents
    Technical Debt Calculator Technical Debt Calculator
    Code Quality Scanner Code Quality Scanner

    Best Practices

    ✅ DO

    • Quantify debt impact
    • Prioritize by ROI
    • Track debt over time
    • Include debt in sprints
    • Document debt decisions
    • Set quality gates

    ❌ DON'T

    • Ignore technical debt
    • Fix everything at once
    • Skip impact analysis
    • Make emotional decisions
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