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Screw Notes, A Really Simple TODO List App

Hacker News

Screw Notes, A Really Simple TODO List App

I've gravitated towards a specific style of writing down lists and notes over the years, so I made a web app that works exactly how I want it to. Then I realised others might like to use a similar tool too, so I product-ised it. I hate complicated task tracking apps, I just want clean pages and to add items as fast as I can type them, just like a real notebook. No due dates, no subtasks, just one way that always works. Why is it called Screw Notes? Because there's a little screw head next to each item showing how done it is. https://screwnotes.com

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Actual performance

2points
1comments
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: apps, tasks, notes · Missing: mac, agents, macos
80%80% 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
66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: apps, way · Missing: mobile apps, ios, personal
59%59% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released
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
40%40% 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
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
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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