A modular Next.js CLI plugin system

Hacker News

Hello HN, I am ad indie hacker, and my first SaaS, Next Inject, is available to try now. Next Inject is a modular CLI plugin system, where you can automate the configuration of features like stripe, metadata, authentication, all in a single click to save your time. And for certain plugins that require environment variables, you will be linked to a docs page to save even more time on configuration. Would love some honest feedback, the metadata plugin is available to use on an empty directory with `npx next-inject add metadata` Daniel P.S. The code for my SaaS is available on github here: https://github.com/DanielCraciunGitHub/next-inject-app

Visit product View on Hacker NewsJul 27, 2024

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Launch Intel predictions

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

71%71% 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: stripe, single, code · Missing: mac, agents, macos

68%68% predicted probability of success on Product Hunt, 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

39%39% 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.

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

26%26% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: saas · 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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