Developer metrics that are actually fair.
Most developer metrics are broken. Lines of code rewards bloat. Commit count rewards small commits. Pull request count ignores complexity entirely. GitSignal takes a different approach: metrics are weighted by estimated effort and analyzed complexity, analyzed by AI that understands code.
How scoring works
GitSignal's AI analyzes every diff for structural complexity, cyclomatic complexity, and pattern recognition. Then it generates four core metrics:
- Hours worked — estimated from diff complexity, not time tracking or commit timestamps
- Impact — how meaningful each contribution is to the codebase and product
- Difficulty — the technical complexity of the work performed
- Efficacy — quality and efficiency relative to the complexity of the task
All scores use weighted averages by hours worked — not simple averages that would let a single easy commit inflate a developer's score.
Why this matters for reviews
Performance reviews shouldn't depend on who speaks up most in meetings or who's best at self-promotion. GitSignal gives engineering managers explainable data grounded in recorded contributions about each developer's contributions — grounded in the actual code, not opinions.
Every score can be drilled down to the individual commits and PRs that inform it. The underlying commits and pull requests remain available for context.
Team comparison
Compare developers side by side across four metrics to discuss where effort and impact are concentrated.
Get started
Replace gut-feel reviews with data. Start free or explore metrics with sample data.
FAQ
Developer metrics questions
What metrics does GitSignal show?
GitSignal shows hours, impact, difficulty, and efficacy estimates for analyzed work, with comparisons weighted by estimated effort.
Should GitSignal metrics be used as a timesheet?
No. The estimates are context for engineering conversations, not a timesheet or a replacement for manager judgment.
Related features
- Automated standups — Daily activity summaries written from your GitHub commits and pull requests.
- GitHub analytics — Feature timelines, work-type distribution, and readable summaries of shipped work.
- Engineering visibility — Ask questions about analyzed engineering activity and see the evidence in context.