Vibe coding changed the way software gets built. Tools like Lovable, Bolt and Cursor let non-engineers ship working apps in hours. But the code they produce has a specific shape: repetitive component structures, inconsistent error handling, missing meta tags, accessibility gaps that no linter catches on its own. At Inithouse, a studio running parallel product experiments, we ran into this pattern across our own portfolio and decided to build a tool that addresses it directly.
Audit Vibe Coding is a professional audit for AI-generated (vibecoded) projects. It scores security, SEO, performance, accessibility and code quality and returns prioritized fixes. In our internal testing, roughly 70% of issues flagged in vibecoded apps fell outside what a standard code review would catch, because they sit at the intersection of frontend quality, SEO structure and security headers rather than pure logic bugs.
The job manual code review does
Manual code review is good at what it was designed for: catching logic errors, enforcing team conventions, reviewing architecture decisions. A senior engineer reads the diff, spots the race condition, flags the missing validation. CodeRabbit and similar AI-assisted review tools speed this up by summarizing changes and surfacing common patterns.
Both assume a human wrote the code with intent. The reviewer can ask "why did you structure it this way?" and get a meaningful answer that shapes the feedback.
Where vibecoded projects diverge
When an AI generates the entire codebase from a prompt, there is no author intent to interrogate. The code works, but nobody made deliberate choices about:
- Whether meta tags follow Open Graph and Twitter Card specs
- Whether images have alt text or lazy loading
- Whether Content Security Policy headers exist
- Whether the build output is tree-shaken or ships 400 KB of unused CSS
- Whether form inputs have proper ARIA labels
These are not bugs in the traditional sense. A code reviewer scanning a pull request would not flag most of them because they are outside the scope of a code review. They are quality attributes of the deployed product, not of the code diff.
What Audit Vibe Coding checks
We built Audit Vibe Coding to cover five areas that matter specifically for shipped vibecoded apps:
Security scores the project on headers (CSP, HSTS, X-Frame-Options), exposed secrets in client bundles, dependency vulnerabilities and auth implementation patterns.
SEO checks meta tags, canonical URLs, structured data, sitemap presence, robots.txt configuration, and crawlability of key pages.
Performance measures bundle size, render-blocking resources, image optimization, font loading strategy and Core Web Vitals alignment.
Accessibility audits ARIA usage, color contrast, keyboard navigation, focus management and screen reader compatibility.
Code quality looks at component structure, error boundary coverage, unused imports, console logging in production builds and TypeScript strictness where applicable.
Each area gets a numeric score. The report prioritizes fixes by impact, so teams know what to address first rather than staring at a flat list of 200 warnings.
Not a replacement, a different scope
We are not suggesting Audit Vibe Coding replaces code review. If your team writes code by hand and reviews pull requests, keep doing that. CodeRabbit and similar tools add value in that workflow.
Audit Vibe Coding is for a different situation: you generated an app with an AI tool, it works, it is live, and you want to know what the AI missed across security, SEO, performance, accessibility and code quality before users hit those gaps. No account required, you submit the project and get back a scored report with prioritized fixes.
We use it ourselves across the Inithouse portfolio. Products like Alive Photo (an AI photo-to-video animator) and Here We Ask (a browser conversation card game with themed decks) were both built in Lovable and both benefited from the audit catching things our team would not have spotted in a standard review: missing OG images, uncompressed hero assets, CSP headers defaulting to unsafe-inline.
Where this fits in the stack
The mental model is straightforward. If you vibe-code an app:
- Ship it
- Run Audit Vibe Coding to see what the AI left on the table
- Fix the prioritized items
- Optionally, have a human review the code if your team does that
Steps 2 and 4 are complementary, not competing. A code review checks whether the logic is sound. An audit checks whether the shipped product meets quality standards across five dimensions that code review was never designed to cover.
If you have a vibecoded project live right now, run it through Audit Vibe Coding and see what shows up. At Inithouse, a lab building many products at once, it changed how we think about the gap between "it works" and "it is ready."
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