Actions Per Minute tracker

Hacker News

Hey HN, Have trouble focusing or getting more done in less time? Train your Actions Per Minute (APM) and increase your execution time, bias towards action, and agency with this web tool. Inspired by Korean pro gamers who train with APM metrics to master StarCraft, this tool applies the same principle to productivity. Whatever you're doing, APM Tracker lets you track how often you're doing it and how much time you've spent unfocused. v1 here requires manual entry for actions, but the goal for v2 is tracked clicks, key presses and session persistence. https://github.com/zkarimi22/actions-per-minute-tracker

Visit product View on Hacker NewsMay 24, 2025

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

91%91% 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 · Missing: plus, platform, intuitive

52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: using · Missing: mac, agents, macos

49%49% 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

45%45% 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

27%27% 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

15%15% 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.

Correct prediction on native model

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