OSS online video downloader for various scoial media platforms

Hacker News

Hi there, I'm a freelance software developer who started that project some time ago. I like to download videos from social media platforms like X (f.k.a Twitter) or Instagram. To do so, one normally visits one of the many download service websites, which are often broken, slow or full of ads. So I decided to develop Squidlr, a website that allows you to comfortable download any video from social media sites. Fast, reliable and without any ads. And open source: https://github.com/rgueldenpfennig/Squidlr Currently I support: Twitter / X Instagram Facebook TikTok LinkedIn In my free time I try to implement the support of additional video platforms. Hope you may find it useful and enjoy!

Visit product View on Hacker NewsJan 16, 2025

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Actual performance

5points

1comments

Did not reach leaderboard

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

87%87% 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.

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

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

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: video · Missing: mobile apps, ios, personal

52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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

Product HuntUnlikely to reach the leaderboard · Strong signals: open · Missing: mac, agents, macos

31%31% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

17%17% 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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