Mastonews, a personal Mastodon RSS feed generator

Hacker News

Hey HN! Author here. I created this app so I could track the personal blogs and websites from the people I follow on Mastodon. It was something that I noticed specially on Mastodon: there were many interesting and quirky websites of the accounts I follow there, stuff that it would be really hard to come by otherwise thanks to search engines enshittification. So Mastonews was the way I found to solve this discoverability problem and to display the feed to me with emphasis in the Mastodon account the website is related to. The website works right away with accounts that have public follows, it only requests an OAuth if your follows are private. If you don't have an account on Mastodon, feel free to use my account to test it out: "henriquelalves@mastodon.gamedev.place" I wrote a bit about my main motivation behind this website on my blog: https://henriquelalves.com/posts/notes-about-making-the-web-... . Feel free to ask me anything or give me feedback on Mastonews!

Visit product View on Hacker NewsAug 30, 2023

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

86%86% 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: new, notes · Missing: mac, agents, macos

59%59% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

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

42%42% 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

12%12% 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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