I made a vi-like modal keyboard plugin for Figma

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I live in Figma, and I’m constantly creating autolayouts, and I tend to know as I’m going what parameters each new autolayout is going to need. Figma gives you shift+a to frame objects into an autolayout, but that’s it. So I built Figmode, which gives you a vi-like modal command layer. So you can type `w` to go into `width` mode and change it to fill/hug/fixed, then ` to back out, then h for height, then spacing, padding, and more. The default keys are optimized such that you can do it all with your left hand, and in nearly all cases without moving your hand. It’s easiest to see it in action: https://www.youtube.com/watch?v=35yQikx1XNs And the plugin itself is here: https://www.figma.com/community/plugin/1638937084194831846 It’s free and open-source, and I’ve been using it for a little while now and have developed a muscle memory that makes it super productive. I’d love to hear any feedback, and hope it’s as useful to y’all as it is to me :)

Visit product View on Hacker NewsMay 28, 2026

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

72%72% 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.

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

50%50% 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: para · Missing: mobile apps, ios, personal

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

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

37%37% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

27%27% 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

14%14% 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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