Compadcn – A CLI wrapper to speed up shadcn/UI component management

Hacker News

I’ve been using shadcn/ui in my projects lately, and while it's great, I kept running into friction using its CLI, it only had add command and no remove command and even add command was so full of friction So I built compadcn: a CLI wrapper that adds interactive add/remove menus, presets, linting for unused components, and safe dependency-aware uninstalling. Still early, open source, and built in TypeScript using Commander, Chalk, and Clack. Would love feedback or ideas from others using shadcn.

Visit product View on Hacker NewsJun 27, 2025

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

87%87% 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.

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

45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

38%38% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: open source, ide, io · Missing: https docs, excited, just released

29%29% 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 · Strong signals: active · 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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