Launch Intel
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Anki Deck Builder

Hacker News

Anki Deck Builder

Hi HN, I built an automatic deck builder for anki. As a non-native english speaker but avid reader, I find that I don't know many words while reading a book. While I can approximate the meaning, it slows me down and many times I move on with ambiguity. Sometimes the words are critical in the context but I don't like to pause and lookup in dictionary. Even if I do, I tend to forget them soon. Also, Anki is the best tool for long term retention but building a deck is cumbersome. So, I built this tool to extract the words from the book I am reading and add those to my anki deck. It is free, give it a try and share your feedback or features you would like to see. Thanks, Pushpankar

Visit productView on Hacker NewsJan 31, 2025
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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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AppSumoStrong fit for a featured deal · Strong signals: soon, builder · Missing: plus, platform, intuitive
65%65% predicted probability of success on AppSumo, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
55%55% 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 HuntOn track for Day 1 leaderboard · Strong signals: context · Missing: mac, agents, macos
51%51% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
27%27% 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
14%14% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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