(yet another) bookmarklet for HN comment threads

Hacker News

I'm one of those many people that enjoy procrastinate-by reading Hacker News. So in a helpless attempt to be productive efficient I've created hnCommentWatcher. Yet another HN bookmarklet. Currently I swear by @mrspeaker's Hackemup bookmarklet [1], it really is brilliant, but its only for the front page, and I still find it painful to follow the comment threads for each individual post (which I believe is where I get the most use (see: intellectual stimulation) out of Hacker News). So this is my solution.

Visit product View on Hacker NewsJan 4, 2012

Share card

Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

Hacker NewsStrong engagement from HN community · Strong signals: hacker news, io · Missing: https docs, excited, just released

53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

51%51% 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

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

34%34% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

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

13%13% 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

Similar products

Threadwatch.xyz – A 'watchdog' for fiery comment threads31%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Threadwatch.xyz – A 'watchdog' for fiery comment threads

Hacker News2

hnuserlist - Browse HN comment threads by username46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

hnuserlist - Browse HN comment threads by username

Hacker News10

OpIn – Comment Anywhere33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

OpIn – Comment Anywhere

Hacker News2

TL;DR for every comment on HN44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

TL;DR for every comment on HN

Hacker News1

Tampermonkey userscript for removing HN threads via predefined regexes50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Tampermonkey userscript for removing HN threads via predefined regexes

Hacker News11

Judge HN Threads with Jev35%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Judge HN Threads with Jev

Hacker News3

Brainfuck with threads and assertions46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Brainfuck with threads and assertions

Hacker News22

I Built Nested Comment Threads with AWS Serverless56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I Built Nested Comment Threads with AWS Serverless

Hacker News4

Voize24%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Comment the Web

Indie Hackers1communication

Chrome extension to collapse HN comment threads into summary sentences30%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Chrome extension to collapse HN comment threads into summary sentences

Hacker News2

Browse all products Analyze your launch