Use case

Prepare your vibe-coded app
for cleanup.

Your app runs. But before you clean up AI-generated code, refactor, or hand it off — you need to understand the architecture, document what exists, and know where to start.

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Who needs vibe code cleanup readiness

Non-technical founders

You used Lovable, v0, Bolt, or Replit to build your MVP and now need a developer to take it further.

Indie hackers

You shipped fast with Cursor or Claude Code and now need to clean up before scaling or onboarding a team.

Devs inheriting AI prototypes

You're taking over someone else's AI-generated codebase and need to understand it before touching anything.

Teams preparing for review

You need shared context before a refactor sprint, code review, or freelancer engagement.

Why AI code cleanup fails without context

AI-generated code often has duplicated logic across files

No documentation means no one knows what's safe to change

Large components with unclear responsibilities

Configuration and environment variables undocumented

Missing test coverage with no plan for what to verify

No architecture map — cleanup becomes guesswork

What to generate before cleanup

Architecture map

A Mermaid diagram showing how modules, routes, and components connect.

Module summaries

Plain-language descriptions of what each folder and file does.

Areas to inspect

Flagged sections that need closer review before making changes.

Cleanup priority list

An ordered list of what to address first, second, and later.

AI-ready context pack

A structured file you can share with Claude Code, Cursor, or Codex.

Missing documentation

Identified gaps in JSDoc, README, and inline comments.

DIY cleanup vs hiring a cleanup specialist

Both work. The right choice depends on your time, budget, and how comfortable you are reading code.

DIY with AI tools

— Lower cost, more time investment
— Works well with Claude Code, Cursor, or Codex
— You stay in control of every change
— Best when you have some technical background

Hiring a specialist

— Faster turnaround, higher cost
— Useful when you need to ship soon
— Needs strong project context to be efficient
— Best when you don't want to read code yourself

What a cleanup specialist needs before starting

Project overview — purpose, stack, entry points

Architecture map showing module connections

Module summaries describing each folder

Risky or complex areas to inspect first

Cleanup priority list ordered by impact

AI context file ready for AI tools

Without this context, even an experienced specialist will spend the first day or two onboarding — billable hours that could go toward actual cleanup.

Common vibe-coded app problems

Duplicated UI logic

Similar components built multiple times across the app.

Unclear API boundaries

Hard to tell where data enters or exits the system.

Scattered config

Environment variables and constants spread across many files.

Oversized components

Single files with 300+ lines doing many unrelated things.

Missing setup docs

No clear instructions for how to run or modify the project.

No test plan

No structured way to verify the app still works after changes.

Cleanup workflows

Clean up yourself with AI

Generate the context pack, then share it with Claude Code, Cursor, or Codex to guide cleanup in small, reviewable steps.

Hand off to a cleanup specialist

Give the specialist your architecture map, module summaries, and cleanup priorities so they can start immediately.

Hire a freelancer or developer

Share the context pack so the developer understands the codebase before writing a single line.

FAQ

What is vibe code cleanup?

Vibe code cleanup refers to the process of reviewing, refactoring, and improving AI-generated or rapidly prototyped code to make it more maintainable, readable, and production-ready.

Do I need a vibe code cleanup specialist?

Not always. If you have development experience, you can use AI tools like Claude Code or Cursor with a good context pack to guide cleanup yourself. A specialist is useful when you need faster results or lack the technical background.

Can LegacyDoc AI clean the code automatically?

No. LegacyDoc AI generates documentation, architecture maps, and context packs. It helps you understand and prepare the codebase — but it does not rewrite or automatically fix your code.

What should I prepare before refactoring AI-generated code?

At minimum: an architecture map, module summaries, a list of areas to inspect, and a cleanup priority list. LegacyDoc AI can generate all of these from your local codebase.

Is this a security audit?

No. LegacyDoc AI does not perform penetration testing, vulnerability scanning, or formal security certification. It helps you understand and document your codebase before cleanup or review.