A GitHub profile is a pile of unstructured signals: repositories, READMEs, commit rhythm, a bio. Reviewers skim it for a few minutes and form an opinion that varies by reviewer and by day. I built Devfolio Analyzer to turn that skim into a structured, weighted evaluation. This article walks through the design: what the code computes itself, what it hands to an LLM, how the output is validated, and where the approach stops being trustworthy.

The short answer

Compute everything that can be computed (language percentages, streaks, presence checks) in plain code. Use the model only for judgments that don't reduce to rules, such as "is this README useful?".…