Documentation
Learn how to measure engineering velocity with AI-powered commit analysis.
Getting Started
Understanding Scores
How Scoring Works
The formula, dimensions, and methodology
The Six Dimensions
Scope, Architecture, Implementation, Risk, Quality, and Performance
Effort Scale Factor
How PR size adjusts scores with tier-based scaling
AI Model Benchmark
How Haiku 4.5, Sonnet 4.6, and Opus 4.6 compare on cost, accuracy, and stability
Score Examples
Worked examples from config changes to system builds
Features
Dashboard Overview
Velocity trends, score distributions, and time-range filters
Pull Request Analysis
Dimension breakdowns, AI summaries, and effort scale factors
Contributors and Profiles
Individual velocity trends, growth tracking, achievements, and leaderboard recognition
Leaderboards and Achievements
Sprint Board, Most Improved, Consistency, and Best of the Best
Historical Backfill
Score past PRs to establish baselines and trends
Repositories
Add repos, view per-repo metrics, and compare repositories
Benchmarks
Compare your team against other engineering organizations on the platform
Configuration
Best Practices
For Engineering Managers
Roll out to your team and use velocity trends effectively
For Engineers
Understand your score and demonstrate impact objectively
Small PRs vs Large PRs
Why PR size matters and how it affects your score
Working in Parallel
How running multiple workstreams boosts your velocity