I made an extension to capitalize words in one click

Hacker News

Hello HN. We often rewrite the same text while only changing its case. It's a tedious and time consuming task. I made an extension that does it in one click. Capitalize either the first letter of a sentence, or the first letter of multiple words, or capitalize all the letters in a selection. This GIF shows how you can use it on Hackernews: https://user-images.githubusercontent.com/57246364/91425009-33bd8780-e878-11ea-8acd-098ba45a8ac3.gif Chrome Store Page: https://chrome.google.com/webstore/detail/apexcase-capitalizer/ijoemkoipbejbfmedlellkdidiopecfg?hl=en It's open source too. Repo: https://github.com/VedantPimpley/ApexCase Feedback would be much appreciated :)

Visit product View on Hacker NewsSep 8, 2020

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

62%62% 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.

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

43%43% 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

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: google, user, new · Missing: mac, agents, macos

36%36% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: open source, io · Missing: https docs, excited, just released

36%36% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

15%15% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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