Technical Debt Audit

Systematically identifies, scores, and prioritizes technical debt across codebases with impact analysis and detailed remediation roadmaps for engineering teams.

Systematic technical debt assessment for engineering teams. Identifies, scores, and prioritizes debt across your codebase with business impact analysis and remediation roadmaps.

What It Does

1. Debt Discovery — Categorizes debt: architecture, code quality, dependency, testing, infrastructure, documentation
2. Impact Scoring — Rates each item on effort (1-5), risk (1-5), and business impact (1-5) using a weighted formula
3. Cost Modeling — Estimates carrying cost per sprint in developer-hours and dollars
4. Remediation Roadmap — Generates a prioritized paydown plan with quick wins, scheduled work, and strategic rewrites
5. Executive Summary — One-page board-ready report showing debt-to-velocity ratio and projected savings

Usage

Describe your system, stack, and known pain points. The agent audits systematically:

text

"Audit our technical debt. We're a Node.js/React SaaS with 180K LOC, 
12 engineers. Known issues: monolithic API, no integration tests, 
3 deprecated dependencies, manual deployments."

Scoring Formula

Priority Score = (Risk × 3) + (Business Impact × 2) + (1/Effort × 1)

Higher score = fix first. Quick wins (low effort, high risk) surface to the top.

Debt Categories

Category	Examples	Typical Carrying Cost
Architecture	Monoliths, tight coupling, wrong patterns	15-25% velocity drag
Code Quality	Duplication, god classes, no standards	10-20% velocity drag
Dependencies	Outdated libs, security vulns, EOL frameworks	5-15% + incident risk
Testing	No tests, flaky tests, manual QA only	20-40% bug-fix overhead
Infrastructure	Manual deploys, no monitoring, snowflake servers	10-30% ops overhead
Documentation	No onboarding docs, tribal knowledge	2-4 weeks per new hire

Output Format

markdown

# Technical Debt Audit Report
## Executive Summary
- Total debt items: [N]
- Estimated carrying cost: $[X]/month
- Debt-to-velocity ratio: [X]%
- Quick wins available: [N] items, [X] dev-days

## Critical (Fix This Sprint)
...

## High Priority (Next 30 Days)  
...

## Scheduled (Next Quarter)
...

## Strategic (Plan & Budget)
...

## Remediation Roadmap
Week 1-2: [Quick wins]
Month 1: [High priority]
Quarter: [Scheduled items]

Why This Matters

Engineering teams spend 23-42% of development time on technical debt (Stripe Developer Report). Most don't measure it. What you don't measure, you can't manage.

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