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See library availabilities for your Goodreads want-to-read list

Hacker News

See library availabilities for your Goodreads want-to-read list

This is a Goodreads + Libby app integration which shows you the library availability for each of the books on your Goodreads want to read list. Basically, I got sick of manually looking up each book on my Want to Read list on the Libby app to see if it was available or how long the wait was. So I made this site which easily gathers all that info for me. At this point, I'm scraping Goodreads to figure out the "Want to Read" list. Libby provides a nice API though. Any feedback is appreciated!! I also have a substack that I'm going to use to post updates, so follow along there if you're interested :) projecttbr.substack.com

Visit product View on Hacker NewsOct 11, 2023

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

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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

54%54% predicted probability of success on Product Hunt, 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

45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

42%42% 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

16%16% 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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