Bi
Big Clock
Hacker NewsBig Clock
It's just a clock, but BIG. Also includes a stopwatch and a timer. I needed a web-based fullscreen clock but all the ones I could find were either ugly, filled with advertising, or way too bloated for my tastes. So I built my own. The clocks are big, but the pages are ultra-minimal: one request and less than 16 kB each. They are coded in plain vanilla JS (ES 5) and CSS (2.1), and designed specifically to work on older devices. They should work back to IE7, though I’ve only test on virtual machines. https://bigclock.app
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2points
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Did not reach leaderboard
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting80%80% 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.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: mac, code, plain · Missing: agents, macos, agent49%49% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal42%42% 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, 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, crypto2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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