Chrome Extension to blur sensitive keywords

Hacker News

I created a Chrome Extension to blur keywords you specified (ex. your name, email and city name etc. ) in websites. The aim of this extension is to make you free to worry showing your sensitive keywords in websites when screen sharing. I would appreciate your feedback. Chrome Web Store: https://chromewebstore.google.com/detail/text-blurrer/mbikoj... GitHub: https://github.com/horihiro/TextBlurrer-ChromeExtension

Visit product View on Hacker NewsMay 27, 2024

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2points

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, email · Missing: mac, agents, macos

63%63% 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.

TrustMRRFits verified-revenue profile · Strong signals: google · Missing: mobile apps, ios, personal

55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

54%54% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Strong signals: created · Missing: supports, reddit linkedin, podcasting

41%41% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

25%25% 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

18%18% 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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