Envyron – reusable env var templates and code snippets

Hacker News

I built *Envyron* to simplify setting up environment variables and generating boilerplate code for new projects. - Define service templates with their environment variables - Combine services into project templates - Generate `.env` files and ready-to-use code snippets (TypeScript, Python, Go) - Mark variables as required or optional for validation It’s *not a secrets manager*, so don’t store production secrets here, it’s just for templates and boilerplate. I’m curious if this way of managing env var templates and generating code snippets makes sense. Any thoughts on how this could be improved or made more intuitive? Try it: https://envyron.vercel.app Github: https://github.com/blackmamoth/envyron

Visit product View on Hacker NewsSep 28, 2025

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

69%69% 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: new, code · Missing: mac, agents, macos

68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

25%25% 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

22%22% 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 · 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

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

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