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FocoDo.Work – A distraction-free focus timer and to-do app

Hacker News

FocoDo.Work – A distraction-free focus timer and to-do app

Hey HN I deployed one of projects: *FocoDo.Work* — a minimal, distraction-free focus timer and to-do list app. I built this to help myself stay focused without the clutter of most productivity tools, and thought others might find it useful too. It’s privacy-first, super simple, and works right in the browser. Features: Add tasks and track time with a built-in timer See the total time you spent working on each task All data is stored locally on your device — no sign-up needed Share your tasks with a quick link across devices or with friends/colleagues Keep the timer visible in a floating picture-in-picture window Full-screen mode for deep work Would love to hear your feedback or suggestions. I’m planning to keep iterating on it! Try it out here: https://focodo.work

Visit product View on Hacker NewsJul 28, 2025

Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

67%67% 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.

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

30%30% 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

29%29% 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

24%24% 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

14%14% 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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