I Created a Chrome Extension for PG: TRAB (Tweet Reporter and Blocker)

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A few days ago I saw this tweet from PG: https://twitter.com/paulg/status/1496549841912094733 ...and guessed it shouldn't be too hard to make a chrome extension to do this (I had never made a chrome extension before) So I took a stab at it - took me a bit over a day to make it, and it was fun to put together. I responded to his tweet with the link to the extension but I'm not sure if he would've seen it. edit: Looks like I missed the approval notification for the listing of this extension on the chrome store: https://chrome.google.com/webstore/detail/trab-tweet-reporte...

Visit product View on Hacker NewsFeb 28, 2022

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

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

best fitHighest predicted score across all platforms for this description.

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

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

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

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

41%41% 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: io · Missing: https docs, excited, just released

30%30% 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

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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