I was tired of opening 2 tabs for every HN link, so I made a userscript

Hacker News

HN is great for the links people share, but a big part of the value I get comes from reading the discussion around them. I realized I was always opening the article in one tab and the comments in another, constantly switching back and forth. I figured there was probably a simpler way, so I threw together this userscript to merge the two. 1. Clicking a link from Hacker News opens the article with a side panel containing the discussion. It doesn't require your credentials, is resizable, and is easy to tweak if you want to customize it. 2. If you land on an article that has previously been shared on HN, the script finds the existing discussion and adds a button in the top-right to open the panel. Feedback welcome.

Visit product View on Hacker NewsJul 28, 2026

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Actual performance

433points

126comments

Made the leaderboard

Launch Intel predictions

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

67%67% 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: exist, existing, hacker news · 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

50%50% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: users, way · Missing: mobile apps, ios, personal

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

AppSumoMay struggle as an AppSumo deal · Strong signals: users · 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

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.

Correct prediction on native model

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