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I made a web color palette generator/editor to simplify color harmony

Hacker News

I made a web color palette generator/editor to simplify color harmony

Hi everyone, I have just finished my free color palette generator that uses your brand colors and creates unlimited palettes based on various color harmonies, that you can then edit and export for use in your projects. I have built it because whenever I would need to select all the shades of different colors for my designs, they never looked quite right. The app is based on the Oklch color space, which means that all different colors will match their lightness. It also groups colors into Accents, neutrals and grays, and comes with features like color contrast checker and colorblindness preview, so you could easily make sure your color palettes are accessible to everyone Check it out here! : https://www.palettemaker.io/create Also, I would appreciate your feedback on what I could improve in my app Thanks, Justas

Visit product View on Hacker NewsMay 29, 2024

Actual performance

4points

3comments

Did not reach leaderboard

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65%65% 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 NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

60%60% 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

41%41% 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

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

29%29% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

14%14% 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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