CodeVibes
AI code review for devs who can't afford CodeRabbit — 80+ detection rules plus DeepSeek AI, from $8/mo.
About
CodeVibes is an open-source (MIT) AI code review tool built by Danish Akhtar that scans GitHub repositories with a hybrid approach: 80+ regex detection rules catch known vulnerability and quality patterns fast, while a DeepSeek-powered AI layer handles semantically complex issues pattern matching misses. Results stream in real time into a prioritized report capped with a 0-100 Vibe Score for overall codebase health. It positions itself explicitly as the budget alternative to enterprise reviewers, charging $8-20/month with healthy gross margins and hundreds of paying users.
The honest picture: it is early-stage — rule coverage is generic compared to enterprise SAST, it cannot reason about custom auth or business-logic flaws, and DeepSeek-backed analysis inherits model hallucinations on edge cases. Still, for solo devs and small shops priced out of the $100+/mo enterprise tier, it is a genuine option.
What it can do
- 80+ regex detection rules for vulnerabilities and bugs
- DeepSeek AI layer for semantic issue detection
- 0-100 Vibe Score codebase health rating
- Real-time streamed analysis reports
- Self-hostable MIT-licensed codebase
- Web, API, and CLI interfaces
Setup
Sign up at the hosted web app, or self-host from the open-source repo. Connect a GitHub repository and run a scan from web, API, or CLI.
Prerequisites
A GitHub account and a repository to scan.
Use cases
Works with
Trust score — 7/10
Scored 7/10 (metrics tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 57; Trending score 66/100 from researcher assessment.
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.