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download all your [Liked] videos from TikTok for safekeeping

Hacker News

download all your [Liked] videos from TikTok for safekeeping

This is a chrome extension I made. You visit tiktok.com and sign in, the extension retrieves MP4s and puts them in a folder. My goal: the TikTok algorithm has helped me find wonderful things. I consider the list of my [Likes] to be a treasure collection, and want to make sure I don't lose them. If you don't have time to try, here's a video walking through all the features: https://youtu.be/BoHOdRxHgP0 Is it free: Yes. (I did test a payment modal once, but users gave me 1-star ratings for it, so I removed it)

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Actual performance

45points
14comments
Made the leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
57%57% 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.
AppSumoStrong fit for a featured deal · Strong signals: users · 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: video, users · Missing: mobile apps, ios, personal
49%49% 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
44%44% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: user · Missing: mac, agents, macos
41%41% 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
23%23% 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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