Related Repos – Discover related open source projects. Updated daily

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Related Repos helps developers to discover open source projects that are related to each other. This can be useful to find alternative or complementary packages when building a full application. Or you can simply surf around in different neighborhoods to find new ideas that you might not have been aware of. Use the official browser extension to quickly view related repos while browsing on GitHub. Data and results are updated daily so you can keep coming back to discover fresh repositories. Results can be thought of as "users who expressed interest in this repository also expressed interest in these other repositories". I hope that you find it useful, any feedback or questions are welcomed! Related Repos - https://relatedrepos.com Browser Extension - https://relatedrepos.com/extension

Visit product View on Hacker NewsAug 15, 2024

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Actual performance

2points

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Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released

60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, open · Missing: mac, agents, macos

55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

25%25% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

13%13% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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