I built a GitHub repository intelligence API — here's what I learned
Every open source maintainer I've talked to has the same problem. Their GitHub issues are a mess. Missing descriptions. No labels. Tickets open for 8 months with zero activity. New contributors picking up issues that turn out to be 3-week architectural rewrites with no warning. The manual triage never ends. So I built RepoAudit — a REST API that audits any public GitHub repository and returns two…
RepoAudit is a REST API that audits public GitHub repositories, providing a data quality report and AI-powered complexity scores for issues. The API was built by the author in TypeScript using Express, separating data quality analysis from AI scoring to improve performance and minimize costs. The quality checks, such as missing descriptions and stale issues, run quickly and cost nothing, while AI scoring is more resource-intensive.
The author learned that batching AI scoring at 20 issues per call prevents latency issues when auditing large repositories. Render's Express rate limiter required setting app.set('trust proxy', 1) to function properly. The API offers three pricing tiers: free, starter, and pro. The author envisions a future GitHub App that automatically scores new issues as they appear, but is currently focused on seeing if the REST API generates sufficient interest before building that feature.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
