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ReadHN, A Hacker News reader with some nice little functionalities:)

Hacker News

ReadHN, A Hacker News reader with some nice little functionalities:)

A Hacker News client with a clean, mobile friendly UI. Features : - bookmark stories. follow discussions / read them later at your convenience. - quickly search for articles using keywords. No more scrolling through the website. - easily managable nested comments. I love the current Hacker News experience and I don't believe my client is in any way a substitute to the original website. Built it over a few days for fun and found myself coming back to it once in a while for some of the features. Wanted to share this with the community. Let me know what you folks think :)

Visit productView on Hacker NewsJul 7, 2022
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Actual performance

5points
1comments
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: new, using · Missing: mac, agents, macos
70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
67%67% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: hacker news, io · Missing: https docs, excited, just released
65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoStrong fit for a featured deal · Strong signals: friendly · Missing: plus, platform, intuitive
57%57% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
20%20% 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
11%11% 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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