Fo

Fontite, an icon font optimization tool for smaller and faster websites

Hacker News

Fontite, an icon font optimization tool for smaller and faster websites

I was frustrated with the state of tooling for working with icons on the web. You're either forced to serve gigantic font files with more icons than you could possibly need, or you have to customize your fonts in a browser-based tool. I wanted a CLI program with a simple configuration format, so that I could integrate it with my static site generator build process and version control. I built fontite to fulfill that need. The linked page demonstrates how you might use it to combine icons from 7 different WOFF2 and SVG sources, and only require about 4kB to serve all of them, with no JS required! I now use this on my personal website [1] and I'm very happy with it. If you're curious, there's more information on the GitLab repo [2] and I wrote up a summary of the making process [3] as well. I'd love to see some smaller, faster websites using this tool! [1] https://antonok.com [2] https://gitlab.com/antonok/fontite [3] https://antonok.com/projects/fontite

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
76%76% 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.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
70%70% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: using · Missing: mac, agents, macos
62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
61%61% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs
31%31% 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
9%9% 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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