A Chrome extension that helps you read articles with minimal scrolling

Hacker News

Whenever I'm reading a long news article on my desktop/laptop, I always wonder why I have to scroll so much when there's so much unused space on the sides. So I decided to make a Chrome extension that uses the CSS3 multi-column layout to make good use of all the screen space available on a desktop/laptop monitor. https://github.com/chaowentan/Purify The article parser that I've implemented is not as robust as other well-known apps such as Pocket, Instapaper, Readability, etc. But I hope this will make people more aware of the usefulness of the multi-column layout in large screens such as desktop monitors.

Visit product View on Hacker NewsJan 5, 2013

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Launch Intel predictions

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

76%76% 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

62%62% 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 · Missing: supports, reddit linkedin, podcasting

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

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

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

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

35%35% 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

19%19% 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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