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Engineering Maturity Model

The Engineering Maturity score is an original, heuristic-based metric designed to reflect how thoughtfully and consistently a developer maintains their public GitHub projects. It is not a measure of “talent”, but of engineering discipline over time.

Repository Hygiene

Evaluates how repositories are organized and maintained. Signals include the ratio of archived to active repositories, presence of abandoned projects, and long-term maintenance behavior.

Consistency of Activity

Measures whether activity is sustained over time rather than bursty. Regular contributions and steady project evolution score higher than sporadic spikes.

Project Depth

Accounts for repository longevity, meaningful iteration, and evidence of real-world usage. Long-lived, iteratively improved projects contribute more than short-lived experiments.

Open Source Engagement

Considers collaborative signals such as forks, stars, and contribution patterns that suggest external usage or community interaction.

Engineering Intent

Rewards evidence of intentional engineering decisions, such as separating experiments from maintained projects, archiving deprecated work, and structuring repositories with clarity.

The final maturity score is an aggregation of these signals, normalized to reduce bias toward repository count, popularity, or language choice. Exact weights may evolve as the model improves.