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Vacation Maximizer – Maximize PTO by taking days off around holidays

Hacker News

Vacation Maximizer – Maximize PTO by taking days off around holidays

Hey! In my last job I was constantly wondering when it would be best to take days off so I could enjoy the most days off in a row, so I made this tool! It tries to schedule PTO around holidays so that you get the most consecutive time off while spending as few days as possible. You can set some constraints, customize the holidays and define mandatory vacation days (in case your company mandates them). If you try for 2025, you should see results for the rest of the year. If there are unscheduled days, it's because there isn't a particularly good period to take them off. (I should make this clearer in the site, to be honest). Let me know if you have any questions or comments and hope you get value out of it! Bernardo

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Actual performance

6points
2comments
Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Strong signals: maximize · Missing: supports, reddit linkedin, podcasting
81%81% 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 HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
42%42% 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
40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
36%36% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
24%24% predicted probability of success on AppSumo, 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
4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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