A
A visual guide to Box Breathing
Hacker NewsA visual guide to Box Breathing
A recent post on HN got me thinking about how to visualize box breathing, and this is the result. I hope you'll find it useful It can easily be installed as an app (PWA) on mobile or desktop for offline/easy access. Instructions are at the bottom of the page. Reference post: https://news.ycombinator.com/item?id=33586383 Source code: https://github.com/lassebomh/box-breathing Happy breathing HN
Share cardActual performance
56points
15comments
Made the leaderboard
Launch Intel predictions
Analyze your own launch →Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: visualize · Missing: mobile apps, ios, personal55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: new, visual, code · Missing: mac, agents, macos39%39% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting32%32% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue16%16% 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, crypto5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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