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Hey HackerNews community! I'm excited to launch analyzemyrepo.com, a free tool to give you actionable insights on the adoption, contributions, diversity, and governance of any GitHub repo. The tool crunches data from over 150k repositories every day to provide valuable insights through charts and text descriptions. The best part? It's open-source! So, if you find it useful, please give it a star on GitHub. Also, don't miss out on the fastest growing repos of the week and the AI-powered GitHub repos search (currently in beta) to easily find the tools you've been searching for, such as "game engines in Rust" or "full-stack Python apps". Give it a try and let us know what you think!

Visit product View on Hacker NewsJan 12, 2023

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Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

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

65%65% 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.

Hacker NewsMay not resonate with HN audience · Strong signals: excited, lua, ide · Missing: https docs, just released, exist

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

nativeThis product was originally launched on this platform.

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

44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

31%31% 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

16%16% 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.

Correct prediction on native model

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