I made an app for the feature every list app is missing

Hacker News

Hi HN! I'm sharing Renli, a reusable checklist app, I know that this could be achieved in several ways in list apps, but I wanted a separate space where I could find all the lists that I'm constantly using (like going on a trip). For now, it's only available for iOS, the Android version is completed, unfortunately, I have an issue with my Google dev account that blocks me from moving forward, if anyone works at Google support and could give me a hand I would appreciate it. I hope some of you can give it a try and find it as useful as I do, I'm happy to read your feedback.

Visit product View on Hacker NewsAug 20, 2024

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Launch Intel predictions

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

82%82% 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 · Strong signals: para, ios · Missing: supports, reddit linkedin, podcasting

61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: ios, apps, google · Missing: mobile apps, personal, entrepreneurs

61%61% predicted probability of success on TrustMRR, 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

37%37% 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

32%32% 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

25%25% 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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