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EasyNPM – Search and install command with one-click for NPM packages

Hacker News

EasyNPM – Search and install command with one-click for NPM packages

I worked on this weekend's project to learn Sveltekit. I thought that it will be good to post here since it could help the developers. Features: Copy installation commands for popular npm managers; yarn, npm, and pnpm with one click. e,g.: yarn add tailwindcss@3.3.3 Bulk package installation: Add to your bag and copy the install command. e.g.: yarn add tailwindcss@3.3.3 vueuse@10.1.0 Advanced filters: Control your result by applying quality, popularity, and maintenance filters.

Visit product View on Hacker NewsJul 25, 2023

Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

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

59%59% 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 HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

46%46% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

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

36%36% 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

32%32% 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

16%16% 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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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