How to evaluate a developer from their GitHub
A practical guide for recruiters and engineering managers: how to read a developer's GitHub activity to judge real skill, what signals matter, and which ones mislead.
A GitHub profile is one of the most honest signals you can get about a developer — but only if you read it correctly. Star counts and follower numbers are easy to see and easy to misread. Real skill shows up in patterns: what someone builds, how consistently they ship, the complexity they take on, and how their code evolves over time.
This guide explains how to evaluate a developer from their public GitHub activity the way SkillProof does it automatically — and how to do it manually if you only have a few minutes.
Start with authored work, not forks
The single biggest mistake is counting forked repositories as the developer's own work. A fork is a copy of someone else's project. It tells you what someone was interested in, not what they built.
Focus on original repositories the person authored. Look at whether they have sustained commit history, meaningful commit messages, and code that solves a real problem rather than tutorial output.
- Exclude forks from any skill judgement.
- Skip empty repos, README-only repos, and single-commit throwaways.
- Weight repositories that other people use (stars, forks from others, real issues).
Read recency as a curve, not a cliff
Recent activity matters, but be careful: a developer who took a full-time job, went on leave, or moved to private repositories is not suddenly less skilled. Treat recency as a smooth signal that fades gradually over roughly two years, rather than a hard cutoff at 6 or 12 months.
SkillProof applies exactly this kind of smooth decay so that scores stay stable and fair instead of lurching when a commit crosses an arbitrary date boundary.
Look at language depth and complexity
Breadth is cheap; depth is expensive. A developer with three years of substantial TypeScript across multiple non-trivial projects is a stronger signal than someone who has touched fifteen languages once each.
Complexity signals — projects with real architecture, documentation beyond a README, tests, and adoption by others — separate hobby code from professional engineering.
Corroborate with other public signals
GitHub is not the whole picture. Public contributions on GitLab, package registries (npm, PyPI, crates.io), Stack Overflow reputation, and competitive platforms can corroborate a developer's strengths. Use them as supporting evidence, never as the sole basis.
Frequently asked questions
Can you evaluate a developer who has mostly private repositories?
Partially. Public activity is the most verifiable signal. SkillProof can also honour a recent employment period from an uploaded CV so developers who moved to private work are not unfairly penalised on recency.
Do stars measure skill?
Not directly. Stars measure popularity and reach, which can correlate with quality but are easily skewed by marketing or a single viral project. Treat them as one weak signal among many.