I built a browser extension with zero dependencies

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If you clicked because of the title, congratulations. It's indeed not fake - I genuinely didn't use any third-party libraries, everything is built using Web APIs and Rust's built-in libraries. Regarding how this project came about - I got quite angry when a browser new tab extension I frequently used got poisoned/had a backdoor implanted. Thus this project was born. As there are still some issues currently, everyone is welcome to provide suggestions and report bugs. It's been open source on Github for a while now - if anyone's interested, feel free to check it out. Thank you all, and happy holidays to you. Github: https://github.com/zayokami/GenresFox Fun fact: I got heavily criticised here (on HN) last time for forgetting to include WASM, and I admit I deserved that criticism at the time. There really is WASM now - if you don't believe me, you can check src/wasm-resize.

Visit product View on Hacker NewsDec 25, 2025

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

79%79% 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.

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

60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released

52%52% 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 · Missing: plus, platform, intuitive

48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

18%18% 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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