Metrics-Based Signals
Measures churn, scatter, follow-up fixes, and commit patterns from your Git history. No guesswork—just data.
What is Codemetry?
Transform Git history into actionable quality insights. Codemetry analyzes your repository and produces a metrics-based "mood proxy" for each day, helping you understand code quality trends without guessing.
What Codemetry Does
Codemetry analyzes your Git repository and produces a metrics-based quality proxy (bad/medium/good) for each day or time window. It measures signals like code churn, file scatter, follow-up fixes, and commit patterns to estimate development strain and quality risk.
Baseline Comparison
Compares each day against your repository’s historical baseline, so “high churn” means high for your project.
Follow-Up Fix Detection
Detects when files get patched shortly after changes—a strong indicator of quality issues or rushed work.
Optional AI Explanations
Enable AI-powered summaries that explain your metrics in plain English. Metrics-only payload—no code is ever sent.
Framework Adapters
Ships with Laravel (Artisan) and WordPress (WP-CLI) adapters. Extensible architecture for additional frameworks.
Privacy-Focused
Runs locally. No code uploads. AI is opt-in and receives only aggregated metrics—never raw code or diffs.
Important: Not Emotion Detection
Codemetry produces a “mood proxy”—a quality/strain indicator based on measurable signals. It does not infer developer emotions, stress levels, or psychological states.
The terms “good”, “medium”, and “bad” refer to code quality risk indicators:
- Good: Normal activity, low follow-up fix density, stable patterns
- Medium: Elevated signals worth monitoring
- Bad: High strain indicators—significant churn, many follow-up fixes, scattered changes
Use these signals to identify periods that may need review, not to evaluate individual developers.
Quick Example
Laravel:
php artisan codemetry:analyze --days=7php artisan codemetry:analyze --days=7 --format=json --ai=1WordPress (WP-CLI):
wp codemetry analyze --days=7wp codemetry analyze --days=7 --format=json --ai=1Sample output:
| Date | Mood | Score | Confidence | Top Reasons |
|---|---|---|---|---|
| 2024-01-15 | good | 78 | 0.80 | Low churn; stable patterns |
| 2024-01-14 | medium | 58 | 0.70 | Elevated fix density; scattered files |
| 2024-01-13 | bad | 35 | 0.75 | High churn p95; multiple reverts |
Next Steps
Installation
Install Codemetry in your Laravel or WordPress project in under a minute.
How it Works
Learn about signals, baseline normalization, and the scoring algorithm.