I analyzed 70k GitHub repos to predict if your PR will get reviewed

Like many of you, I've spent days debugging an open issue in an OSS repo, writing unit tests, making sure CI is green, and opening a clean PR with detailed reproduction notes—only for it to sit in review silence for 9 months until a bot eventually closes it as "stale."

GitHub stars and follower counts don't tell you anything about whether a project actually welcomes outside contributions:

• junegunn/fzf (83k stars, Go): Maintains an incredible 82.6% community merge rate with first responses often landing in under an hour.

• caddyserver/caddy (78k stars, Go): A responsive A-Tier reo with a 51.4% merge rate and active maintainer feedback cycles (~11h).

• istio/istio (38k stars, Go): An S-Tier powerhouse with a 70.8% community merge rate and a median first response under 7 hours.

• home-assistant/core (91k stars, Python): S-Tier, merging 68.8% of external PRs with ~2h response times.

• strelov1/freehire (3.4k stars, Go): S-Tier with a 87.5% merge rate.

• Many 50k+ star projects look active on paper, but 99% of merges are internal team commits; community PRs go straight into the graveyard.

I built GetMerged (https://getmerged.abhishekco.de) to surface maintainer review telemetry before you fork.

• C-Rank (Contributor Readiness Score): A 0–100 rating that separates welcoming projects from ghost towns based on real external PR merge rate, median review latency (p50/p90), and reviewer bus factor.

• Welcoming Rankings by Language: Curated leaderboards across Go, Rust, Python, TypeScript, etc., filtered by tier and active review signals.

Build it with Go + Next.js (SSR) + MySQL.

Try looking up a repo you frequently contribute to or maintain. I'd love your honest (and brutal) feedback on the scoring metrics. What other signals would save you from opening doomed PRs?