Aj Geddes Useful AI Prompts Technical Debt Assessment

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:

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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