NvEnvy – A Notational Velocity (NvAlt) Reboot in Swift. OSS

Hacker News

I'm a long time user of Notational Velocity and then nvAlt, and tried nvUltra recently but in the world of Claude it felt like I should own my own——change behaviors as I need them. Right now it's just a Mac app, but iOS coming in the future for myself, sync with icloud. Notes are saves as .md files and have quick search. You can open the same folder with Obsidian if that's your jam (Obsidian always felt slow and clunky to me, I know folks love it though, so keeping it compatible). The app is very simple, just plain text. We don't even render markdown right now, though it's coming. Definitely vibe coded. Definitely will need some updates, but share it before it's polished.... PRs appreciated.

Visit product View on Hacker NewsMay 29, 2026

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Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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

94%94% 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: ios, compatible · Missing: supports, reddit linkedin, podcasting

76%76% 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: io · Missing: https docs, excited, just released

38%38% 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 · Strong signals: ios, way · Missing: mobile apps, personal, entrepreneurs

38%38% 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

37%37% 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

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.

Correct prediction on native model

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