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byline a vim tailwind CSS editor

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byline a vim tailwind CSS editor

Hello fellow hackers. I've reached that point in this little passion project where I could use some feedback. I'm a long time vim user and a recent student of the tailwind css system. I wanted a few things: 1. Never have to close a tag or type the word "class" or quotes. 2. See an instant preview of what the rendered HTML looks like on screen. 3. Use normal vim commands to make small edits. 4. Get a popup menu with common tailwind classes to add as you type. 5. Be able to "zoom in" to a child node and make it temporarily the root node. (Hit Enter for this feature, and up arrow to get back to normal parent node.) I have it running here: https://andrewarrow.dev/ Video demo here: https://www.youtube.com/watch?v=E0dd9SzI9Ro All open source MIT license: https://github.com/andrewarrow/byline You might think a lot of javascript/typescript went into this project but oh-no! This is all golang wasm (web assembly). Feedback most welcome on what features should be added next OR go ahead and tell me this is all just a bad idea for reasons x y and z. Please and thank you.

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, open · Missing: mac, agents, macos
84%84% 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 · Missing: supports, reddit linkedin, podcasting
84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released
57%57% 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: video · Missing: mobile apps, ios, personal
43%43% 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
33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit
17%17% 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.

Incorrect prediction on native model

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