Text only reader mode designed for eye comfort and focus

Hacker News

Hi! I just created my first Chrome extension. I know it's simple and basic, but I really enjoy using it and would love to share it with you! Design Principles - Low-glare background : Uses a soft, sepia-like background to cut glare and reduce eye strain during long reading sessions. - Adds breathing room between lines to make text easier to follow and more accessible. - Keeps lines at a readable width to help with focus and reduce eye movement fatigue. - Uses clean, screen-friendly fonts like Verdana and Helvetica that are easier to read online. Limitations : is designed for reading plain text articles. Because it hides images, tables, and formulas, some pages may lose important context or meaning. Chrome Web Store : https://chromewebstore.google.com/detail/comfortview/npojnlh...

Visit product View on Hacker NewsOct 20, 2025

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

89%89% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: google, context, using · Missing: mac, agents, macos

56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: friendly · Missing: plus, platform, intuitive

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

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

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

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

36%36% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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