Roots – A Minimal Habit Tracker That Grows a Garden

Hacker News

Hey HN I know — no one’s really asking for yet another habit tracker But I built Roots as a minimalist side project to learn full-stack web dev and improve my product/UX skills. It’s inspired by the Streaks app — but instead of a grid of icons, your habits grow into a garden Complete rituals → grow a tree. Miss days → your forest fades. What it includes: Daily ritual tracking Visual streak system (6 tree stages) A friend feature (you can view their garden too) Clean UI, no ads, no upsells — just free I’m planning to build a mobile + Apple Watch version soon, with more streak-oriented mechanics, faster habit check-ins, and deeper personalization. Would love feedback before I go deeper into that phase. Here’s the live version: https://www.rootsgarden.space

Visit product View on Hacker NewsApr 30, 2025

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

72%72% 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

69%69% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

51%51% 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 · Strong signals: soon · Missing: plus, platform, intuitive

47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

43%43% 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

22%22% 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.

Incorrect prediction on native model

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