Scrolodex – A super simple window switcher for macOS

Hacker News

I built scrolodex to scratch my own itch of having a quick and simple way to switch between the currently open windows under my cursor. Simply hold ⌥ + scroll to cycle through windows under your cursor. Release to focus. Also includes triggers for scrolling through all windows, dock app's windows, or switching between desktop spaces. Configurable hotkeys, themes and overlays. Completely free and OSS. brew install --cask jaydenfyi/tap/scrolodex Website/demo: https://scrolodex.app/ GitHub: https://github.com/jaydenfyi/scrolodex

Visit product View on Hacker NewsMay 28, 2026

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Actual performance

4points

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, cursor · Missing: agents, agent, claude

79%79% predicted probability of success on Product Hunt, 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

51%51% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released

48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

33%33% 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

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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