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Afrexai Tech Debt Audit

Technical Debt Audit

1kalin0 installations selon la source☆ 0 Étoiles du dépôt

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install 1kalin/afrexai-tech-debt-audit

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

Instructions

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Dependencies Outdated libs, security vulns, EOL frameworks 5-15% + incident risk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

# Technical Debt Audit Report
## Executive Summary
- Total debt items: [N]
- Estimated carrying cost:...

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/1kalin/afrexai-tech-debt-audit
Version
—
Commit
60ef12ef699c1753f0278853d7378b3fc2fd44cf
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

README

Technical Debt Audit

Systematic technical debt assessment for engineering teams. Discovers, scores, and prioritizes debt across your entire stack with dollar-cost estimates and a remediation roadmap.

Most engineering teams spend 23-42% of their time on tech debt but never measure it. This skill turns vague "we should refactor" conversations into a scored, prioritized action plan with real cost numbers.

Features

  • 6-category debt taxonomy — architecture, code quality, dependencies, testing, infrastructure, documentation
  • Weighted priority scoring — risk × 3, business impact × 2, inverse effort × 1
  • Carrying cost estimates — dollars per month, velocity drag percentage
  • Remediation roadmap — quick wins → scheduled work → strategic rewrites
  • Executive summary — board-ready one-pager with debt-to-velocity ratio

Who It's For

  • Engineering managers tracking team velocity
  • CTOs presenting debt reduction plans to the board
  • Tech leads prioritizing refactoring work
  • Agencies auditing client codebases before taking over

Quick Start

Install via ClawHub, then describe your system and known pain points. The agent handles the rest.


Built by AfrexAI | AI Revenue Calculator | Agent Setup Wizard

Contenu extrait

SKILL.md
# 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:...
README
# Technical Debt Audit

Systematic technical debt assessment for engineering teams. Discovers, scores, and prioritizes debt across your entire stack with dollar-cost estimates and a remediation roadmap.

Most engineering teams spend 23-42% of their time on tech debt but never measure it. This skill turns vague "we should refactor" conversations into a scored, prioritized action plan with real cost numbers.

## Features

- **6-category debt taxonomy** — architecture, code quality, dependencies, testing, infrastructure, documentation
- **Weighted priority scoring** — risk × 3, business impact × 2, inverse effort × 1
- **Carrying cost estimates** — dollars per month, velocity drag percentage
- **Remediation roadmap** — quick wins → scheduled work → strategic rewrites
- **Executive summary** — board-ready one-pager with debt-to-velocity ratio

## Who It's For

- Engineering managers tracking team velocity
- CTOs presenting debt reduction plans to the board  
- Tech leads prioritizing refactoring work
- Agencies auditing client codebases before taking over

## Quick Start

Install via ClawHub, then describe your system and known pain points. The agent handles the rest.

---

Built by [AfrexAI](https://afrexai-cto.github.io/context-packs/) | [AI Revenue Calculator](https://afrexai-cto.github.io/ai-revenue-calculator/) | [Agent Setup Wizard](https://afrexai-cto.github.io/agent-setup/)

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