Fi

Find alternatives to almost any popular GitHub repo

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Find alternatives to almost any popular GitHub repo

Several months ago, I built a "stealth" feature that I could use. It hasn't been advertised, and I've been the only user. As I find it useful for myself, I believe others (software developers) may like it too. So, this is the first public post about it, and if it gets any positive feedback, I may put some time into promoting it more. In essence, given that you've opened a GitHub repo (there are ~225k of the more popular ones indexed as of now), you can replace "github" with "libhunt" within the URL, and you will find the top alternatives and related projects. For example, here are three popular repos: - https://github.com/rails/rails - https://github.com/vercel/next.js - https://github.com/kovidgoyal/calibre To test it out, open any of the examples above and replace "github" with "libhunt" within the browser URL. You can also try with any other repository as long as it's a bit popular. I'd be more than happy to answer any questions and receive some feedback. Thanks!

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, open · Missing: mac, agents, macos
76%76% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
67%67% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
66%66% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal
31%31% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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