Similarity = cosine(your_GitHub_stars, Karpathy) Client-side
GitHub profile analysis - Build your embedding from your Stars - Compare and discover popular people with similar interests and share yours - Generate a Skill Radar - Recommend repositories you might like
Similarity = cosine(your_GitHub_stars, Karpathy) Client-side launched on January 6, 2026 with 172 votes, #171 of 14,585 launches that month and more than 95% of that year's launches.
In plain words
Similarity analyzes GitHub profiles by creating numerical representations based on a user's starred repositories. It compares these embeddings to find people with similar coding interests and recommends repositories that align with those interests. The tool also generates a skill radar visualization showing technical areas of focus. It runs entirely in the browser and allows users to share their profile analysis with others.
written from the facts on this page · September 2026
From the sources
Discover your "Developer Soulmate" by analyzing your GitHub Stars. Compare your GitHub profile with legends like Andrej Karpathy. Get a visual Skill Radar, find hidden gem repositories based on your interests, and share your profile with friends. Runs 100% locally in your browser using WASM.
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GitHiredDec 2025 · githired.tech · ▲360Hey HN - today I’m launching GitHired. A hiring platform that ranks developers based on what they actually build — not what they claim on a PDF. It’s called GitHired, and here’s the core idea: GitHub > Resumes Instead of trusting “proficient in React” bullet points, we analyze a candidate’s actual GitHub: their real tech stack their most complex projects how active they are what kinds of contributions they make which skills match your job description and yes, we detect fake “green square farming.” Why we built this Because engineering hiring is broken. Resumes are inflated. Activity charts…
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Since everyone seems to be making a github application, I thought I'd share mine. It's an aggregated view of all of a given person's github projects, as well as easyish lookups for linkedin/stackoverflow/hackernews. It attempts to determine both productivity (how much code did this person write?) as well as impact (did anyone care?) I'd love any feedback, but go easy on the number of simultaneous searches as I'm trying to play nice by github's api limits. check it -- http://www.gitalytics.com
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