--- name: afrexai-tech-debt-audit description: "Technical Debt Audit" --- # Technical Debt Audit 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: ``` "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velocity drag | | Code Quality | Duplication, god classes, no standards | 10-20% velocity drag | | Dependencies | Outdated libs, security vulns, EOL frameworks | 5-15% + incident risk | | Testing | No tests, flaky tests, manual QA only | 20-40% bug-fix overhead | | Infrastructure |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. --- Built by [AfrexAI](https://afrexai-cto.github.io/context-packs/) — AI-powered business operations tools. Need the full engineering context pack? Browse our [AI Context Packs](https://afrexai-cto.github.io/context-packs/) ($47) or try the free [AI Revenue Calculator](https://afrexai-cto.github.io/ai-revenue-calculator/).