Kokoro – A simple app to manage chores and allowances for kids

Hacker News

I built Kokoro to solve a real problem in my own family: getting kids to do chores consistently and understand the value of money. It’s a lightweight web app that helps parents assign tasks, track what gets done, and automate weekly allowance payouts based on completed chores. It’s built with React, TypeScript, and Tailwind—lean, fast, and mobile-friendly. I’m not trying to gamify parenting or replace conversations—just give families a tool that makes consistency easier and keeps the mental load manageable. Would love feedback from other parents or developers working on similar “family ops” problems.

Visit product View on Hacker NewsJul 30, 2025

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

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

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

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

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

41%41% 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

31%31% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

20%20% 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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