Notifier – Keep track of your favorite dependencies

Hacker News

Hi HN, We are Anil and Yilmaz from the team behind Notifier. Notifier is a macOS menu bar app that keeps track of your favorite packages and notifies you whenever a new version is available. You can currently track packages from npm, pub.dev, packagist, OpenUPM and the Unity asset store. We plan to add more package repositories very soon. Notifier can also watch your dependency manifest files to make it simple to keep track of the packages you use in your projects. We have many new features planned such as tracking software and SDK versions. We want to offer HN an early look at Notifier in hopes that you can help us test the application before we launch it fully. We're grateful for any feedback you might have for us. Website: https://notifier.dev/

Visit product View on Hacker NewsMar 30, 2023

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Actual performance

5points

Did not reach leaderboard

Launch Intel predictions

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

74%74% 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

63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

38%38% 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 · Missing: mobile apps, ios, personal

35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

19%19% 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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