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templUI – The UI Kit for templ (CLI-based, like shadcn/UI)

Hacker News

templUI – The UI Kit for templ (CLI-based, like shadcn/UI)

Hi HN, I’m building templUI – a UI kit for templ, styled with TailwindCSS. It includes a CLI installer to add and manage components (like: templui add button modal) – inspired by shadcn/ui. templUI – The UI Kit for templ Goals: - Help Go devs build UIs faster with well-structured, minimal components - No JS frameworks – just Vanilla JS - HTMX-friendly, but optional - CSP-compliant by default - Built for enterprise use and long-term scaling Currently at v0.7x, with 1000+ commits and 500+ GitHub stars. It's already used in production projects and evolving fast. * Website: https://templui.io * GitHub: https://github.com/axzilla/templui Happy to hear feedback or ideas!

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Actual performance

62points
34comments
Made the leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · 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.
Hacker NewsStrong engagement from HN community · Strong signals: ide, 000, io · Missing: https docs, excited, just released
54%54% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
52%52% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: friendly · Missing: plus, platform, intuitive
40%40% 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
36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% 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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