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Magicreader – shorten and simplify web articles in-place

Hacker News

Magicreader – shorten and simplify web articles in-place

Hey HN! This is Michael from magicreader. We’ve just released a Chrome extension that enables you to read web articles in the style and length you prefer. The idea is similar to Violentmonkey/Tampermonkey and Tweeks, but focused on reading. For example, let’s say you want to read a research paper online, but you’re not an expert in the domain. You can use magicreader to rewrite the paper for a general audience and swap this simplified version directly into the page. While you’re reading, you can seamlessly flip back and forth between the simplified version and the original. How this is different from using Claude/ChatGPT: with magicreader, there’s no need to copy-paste the text into a chat window, and there is no sidebar. Instead, the HTML of the article simply changes in-place, maintaining the core reading experience. We currently support the following use cases: - Shorten: shorten web articles in-place to read 4x faster - Simplify ("ELI5"): adapt specialist writing (e.g., research papers) for a general audience - De-spin ("Honest"): annotate marketing/PR materials to quickly spot unsupported claims - Clean: rewrite unclear or old-fashioned writing in a clean, modern style Notes: - We don’t bypass paywalls. We only operate on text you can already view in your browser. - When you rewrite a webpage, we send the full HTML to our backend; the rewritten text is then locally stored in your Chrome extension storage. The extension only sends data to the backend when you actively invoke magicreader. We don’t track your browsing activity across pages. - We use AI to rewrite content, and AI can make mistakes. That’s why we made it easy to flip back and forth between the rewritten version and the original—without losing your place in the text. Rewriting full web articles using large language models is expensive, so we’re offering a limited free tier plus two paid plans. We’re planning to expand the free tier by using smaller and on-device LLMs. Demo video: https://youtu.be/pckMSxCFUDo Chrome extension: https://chromewebstore.google.com/detail/magicreader/phncpke... We'd love feedback, particularly on 1) which reading mode is most useful, 2) where it breaks on real sites, and 3) any suggestions you have for new features. You can reply directly here or email me at michael@magicreader.com.

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86%86% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
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Indie HackersFits the IH revenue-focused audience · Strong signals: mistakes · Missing: supports, reddit linkedin, podcasting
79%79% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: just released, ide, io · Missing: https docs, excited, exist
56%56% 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: plus · Missing: platform, intuitive, reviews
45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video, google · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · 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 · Strong signals: chat, paid · Missing: web3, crypto, cryptocurrency
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