Hacker Smacker

Hacker Smacker

Highlight (friend) and filter (foe) individual authors on Hacker News

What is Hacker Smacker?

Hacker Smacker is an Edge add-on that allows you to highlight and filter individual authors on Hacker News. It helps you identify quality commenters and reduce the time spent on Hacker News by quickly finding the good stuff.

Users: 216 ▲ 4
Rating: 3.00 (2)
Version: 1.0 (Last updated: 2021-04-29)
Creation date: 2021-04-29
Risk impact: Low risk impact
Risk likelihood: Low risk likelihood
Manifest version: 2
  • https://news.ycombinator.com/
  • http://news.ycombinator.com/
  • http://www.hackersmacker.org/
  • https://www.hackersmacker.org/
Size: 46.62K
URLs: Website
Stats date:

Other platforms

Not available on Chrome
Not available on Firefox
Want to check extension ranking and stats more quickly for other Edge add-ons? Install Chrome-Stats extension to view Chrome-Stats data as you browse the Edge Add-on Store.
Chrome-Stats extension

Hacker Smacker helps you identify quality authors and filter out obnoxious commenters on Hacker News. Three little orbs appear next to every author's name and you can choose to either friend or foe them.

What's neat is that if you friend people, and they also use Hacker Smacker, you'll see all of your friend's friends and foes. This helps you identify commenters that you want to read as you quickly scan a comment thread. I've found that this reduces the time I spent on Hacker News, as I can glance at long comment threads and just find the good stuff.

Hacker Smacker is directly inspired by Slashdot's friend/foe system. Hacker Smacker is also open-source and is available on GitHub.

User reviews
it does not work i'm leaving
by Toby, 2021-09-13

Great way to read Hacker News and easily spot the good comments.
by Sam, 2021-05-18
View all user reviews
Risk impact

Hacker Smacker is relatively safe to use as it requires very minimum permissions.

Risk likelihood

Hacker Smacker has earned a fairly good reputation and likely can be trusted.

Upgrade to see risk analysis details