Xcuts – A package manager, shell, and more, made in iOS shortcuts

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Xcuts is a programming tool designed to help people create shortcuts (or javascript programs), and to be able to package and run them. It took me a while to iron out all the issues. I added tons of features to Xcuts, including: - a way to run js programs, which can depend on js libraries, in ShortTerm - lots of commands, such as: head/tail, touch, mkdir, file, date, echo, wget, cd, qlook, exit, mail, grep, rm, ls, cp, sort, cat, mv, and $SB (.sbundle archive editor and text editor). - automatic recursive dependency resolving and autoremoving - a core unix-like filesystem stored in iCloud drive/Shortcuts/ROOTFS or, in ShortTerm, simply /ROOTFS. - a program that lets you display html and create callbacks to the shortcuts app that can make changes to the html displayed (UICuts). This is all written in shortcuts, so that means you don't have to install any apps. In additon, it's offline and you don't have to connect to anything. I recorded some demo videos: [ https://www.icloud.com/sharedalbum/#B2d5oqs3q2kl8t2 ]. One of the videos showcases something I ported to Xcuts, called csvf ( https://github.com/matthew-james-brewer/csvf ). It's written in javascript + shell script. I've been working on this for a while. What do you think of it?

Visit product View on Hacker NewsOct 25, 2025

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

88%88% 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 HuntOn track for Day 1 leaderboard · Strong signals: apps · Missing: mac, agents, macos

82%82% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: filesystem, ide, io · Missing: https docs, excited, just released

75%75% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: ios, apps, video · Missing: mobile apps, personal, entrepreneurs

57%57% 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

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

22%22% 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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