Website analyzer weights
| Category | Weight |
|---|---|
| Template Detection | 14% |
| Modern AI | 18% |
| Naming Patterns | 7% |
| Dependencies | 9% |
| AI Copywriting | 20% |
| UX Depth | 13% |
| Security | 10% |
| AI Analysis | 9% |
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Documentation
How VibeDetect analysis works
This page explains how the vibe code detector combines analyzer evidence into a score. If you are using VibeDetect as an AI generated website checker, this is the reference for how weighting and verdict thresholds are applied.
Scoring process
- 1. Run website or repository analyzers and capture category scores with confidence.
- 2. Normalize analyzer weights and compute contribution points.
- 3. Apply safety floors for strong direct signals where relevant.
- 4. Map final score to a verdict range.
Repository analyzer weights
| Category | Weight |
|---|---|
| AI Analysis | 15% |
| AI Config | 11% |
| Velocity | 10% |
| Evolution | 10% |
| Code Quality | 9% |
| Git Workflow | 8% |
| Commit Patterns | 7% |
| Security | 7% |
| Test Coverage | 7% |
| File Structure | 5% |
| Social Patterns | 5% |
| Dependencies | 3% |
| README Quality | 3% |
Verdict thresholds
up to 24
Likely Human-Built
up to 49
Some AI Signals
up to 74
Probably Vibe Coded
up to 100 (inclusive cap)
Almost Certainly Vibe Coded
FAQ
How should I read the final VibeDetect score?
Scores range from 0 to 100. Don't read into it too much! It's only meant to be a bit of fun and a slight guide. Lower scores indicate more human-like patterns, while higher scores indicate stronger AI-generated or vibe coding signals.
Does VibeDetect use only AI models to classify code?
No. Heuristic analyzers always run first. Optional LLM analyzers are additive and intended to supplement deterministic signals.
Can false positives happen in detect AI code workflows?
Yes. Repeated design systems, mature templates, or deliberate style choices can resemble AI-assisted output. Treat results as a review aid, not final proof.