I made an extension to comment on any website

Hacker News

Hello HN, One of the great things about HN is being able to see what other people think in the discussion. I find it exciting to read the comments and follow the conversations. Unfortunately, not many websites enable people to leave comments. Some of them filter and control what people are allowed to say (e.g. reviews). I thought it would be great to be able to comment on any website. So I made an extension that lets you comment on any website. The extension shows up as a small icon on the side of the webpage. It can be expanded so that you can leave your own comment, and see what other people have said. The extension only uses the URL of the current website, and it does not track any of your activity. Moreover, the comments you make are completely anonymous. I would love to hear your opinion about this!

Visit product View on Hacker NewsFeb 12, 2023

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Actual performance

2points

3comments

Did not reach leaderboard

Launch Intel predictions

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

75%75% 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.

Hacker NewsStrong engagement from HN community · Strong signals: ide, 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.

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

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

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

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

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

34%34% predicted probability of success on TrustMRR, 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

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

Incorrect prediction on native model

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