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I built a tool to clear my YouTube's "Watch Later" Video Graveyard

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I built a tool to clear my YouTube's "Watch Later" Video Graveyard

I built this because I consume a lot of technical lectures and long-form podcasts on YouTube, but I found myself wasting hours scrubbing through videos just to find specific citations or concepts. Recapio is a tool that extracts the transcript and generates structured summaries for videos (and web articles). It’s not trying to replace watching content, but rather to act as a 'Ctrl+F' for video context. One technical challenge I faced: Dealing with auto-generated YouTube captions vs. forced captions was messy. I had to build a parser that normalizes the timestamps so that when you click a summary point, it actually seeks to the correct frame, even if the caption timing is drifting. It has a free tier that should cover most casual usage. I’d love your feedback on the extraction quality

Visit productView on Hacker NewsDec 23, 2025
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Launch Intel predictions

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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.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: context · Missing: mac, agents, macos
58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video · Missing: mobile apps, ios, personal
36%36% 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
24%24% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
21%21% 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.

Correct prediction on native model

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