An evidence-based platform to find great developers, measure where you stand, and grow from there. Start with a brutally honest 0–100 value & trust score on any public GitHub profile — see your gaps, learn where to go, then explore the strongest builders in your ecosystem, find worthy peers and rivals, and let your own work get discovered.
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Maker
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I'm hikariming, the developer behind ghfind.
The backstory: A few months ago I was evaluating candidates for a project and kept running into GitHub profiles that looked incredible on the surface — thousands of stars, dark-green contribution graphs, hundreds of followers. But when I actually looked at the repos, most of the stars were on forks, the contributions were one-line typo fixes across repos they didn't own, and the followers had the unmistakable curve of a follow-back loop.
I realized GitHub's built-in metrics — stars, followers, contribution count — measure popularity, not contribution value. And popularity is cheap to manufacture.
So I built ghfind. It scores any GitHub account from 0–100 across six weighted dimensions: account maturity, original project quality, contribution quality, ecosystem impact, community influence, and activity authenticity. The engine is fully deterministic — same inputs, same score, every time. No AI touches the number. The scoring core is open source under AGPL, ported line-for-line from Python to TypeScript with unit tests locking the outputs in parity.
A few things you might find interesting:
Out of ~19,000 scored accounts, fewer than 1% tripped the strongest red flags. Most developers are genuine. But the ones that aren't are spectacularly not.
Stars have almost zero correlation with contribution quality. I've seen accounts with 8,000+ stars and contribution scores in the bottom quartile — all forks, no original work.
The optional AI roast is the part everyone tries first. It's brutal. You've been warned.
You can bring your own LLM key (stays in your browser localStorage, never hits the server), use the REST API, the CLI (ghfind scan), or plug it into any MCP-compatible agent.
What I'd love feedback on:
Scoring edge cases — if your score feels off, tell me. The engine gets smarter with every real-world data point.
Language leaderboards — which languages should I add next?
Anything broken, confusing, or just not fun.
Try it on yourself first (everyone does): ghfind.com
Then try some usernames you admire — and some you're suspicious of. That's where it gets fun.
Happy to answer any questions. Really excited to hear what you all think! 🔥
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How do you actually calculate the trust score, and does it look at things like commit history depth or just surface-level repo activity?
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How do you actually calculate the trust score - is it mostly based on commit history or are you weighing in things like code review activity and collaboration signals too?
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The score on my profile was a little humbling but the breakdown actually told me something I didn’t know about my own repos. Worth poking around for a minute.
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Ran my own profile through it and the breakdown was uncomfortably specific in a good way, finally know which repos actually count toward trust vs the throwaway forks cluttering my graph.
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how does the scoring actually work under the hood, like is it purely commit volume or does it factor in code quality and project impact too
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love how it just gives you a number right away, no fluff or long onboarding. the brutal honesty angle makes the score feel earned instead of another vanity metric.
How do you actually calculate the trust score, and does it look at things like commit history depth or just surface-level repo activity?
How do you actually calculate the trust score - is it mostly based on commit history or are you weighing in things like code review activity and collaboration signals too?
The score on my profile was a little humbling but the breakdown actually told me something I didn’t know about my own repos. Worth poking around for a minute.
Ran my own profile through it and the breakdown was uncomfortably specific in a good way, finally know which repos actually count toward trust vs the throwaway forks cluttering my graph.
how does the scoring actually work under the hood, like is it purely commit volume or does it factor in code quality and project impact too
love how it just gives you a number right away, no fluff or long onboarding. the brutal honesty angle makes the score feel earned instead of another vanity metric.