Monoco – smooth squircle corners for HTML elements

Hacker News

I work at a design agency where UX/UI designers regularly use so-called "smooth corners", or "squircles". It happens more often now that Figma supports these natively. When handing over the designs to development, they quickly hit a roadblock, because CSS only supports regular rounded corners. I've made a tiny tool for these exact situations. Now you can add your own corners to your own shapes in vanilla JS, React or Svelte.

Visit product View on Hacker NewsDec 14, 2024

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: tiny · 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 · Strong signals: supports · Missing: reddit linkedin, podcasting, created

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: 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.

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

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

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

40%40% 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

16%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, crypto

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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