Shifu – A pure POSIX shell framework to create powerful CLIs

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The startup I work for has an internal, bash-based, cli that basically amounts to shared aliases with a common entrypoint. As the number of aliases has grown, I've had a desire to group functionality together in subcommands, add more help strings, and have better tab completion. I know I could convert it to, e.g., a python script, but I was curious what was possible if we continued to use bash. I couldn't find anything that solved those problems without lots of extra machinery. I understand why, shell scripts are generally not long, and focused on a dedicated task; adding cli features to them is mostly unnecessary, many might even discourage it for many valid reasons. Nonetheless, I considered writing this functionality myself, but that felt like a poor use of company time. So I started toying with what a framework to handle those concerns entirely in shell script would look like on the side. Thus, shifu was born. I've been working on it off and on for about a year, and think I've got a reasonable alpha release, so thought I'd share.

Visit product View on Hacker NewsMar 30, 2026

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

81%81% 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 · Strong signals: started · Missing: supports, reddit linkedin, podcasting

79%79% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

63%63% 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 · Missing: mobile apps, ios, personal

46%46% 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

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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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