Chappie – Direct Desktop Search and macOS Control

Hacker News

*Chappie (Desktop Search)* is a local search and control input box. It is optimized for—and excels at—speedily launching apps and opening folders from common folders. * Chappie owns `⌘+SPACE` when running. * Quickly launch apps and open folders. * Press `ENTER` to open, add `⌥` to open in terminal. * Configure custom shortcuts like `?` to search the web. * A dozen shortcuts out of the box. * `/` tab through directories. * `!` commands (volume, brightness, etc.) and settings. * `=` to calculate, ENTER to copy the result. * All at just ~2.3 MB on disk. * *Chappie (Files)*, a supplement to Finder, is also in the works. Closed source for now, but planning to open-source at 1.0. I want the code to be well-documented and easy to follow at the time of the 1.0 launch. But in the meantime, I’d sincerely appreciate any help in making this great for us all to enjoy.

Visit product View on Hacker NewsJun 29, 2026

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

97%97% 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

84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

38%38% 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

34%34% 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

17%17% 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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