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Git-based front-end interface for Hugo

Hacker News

Git-based front-end interface for Hugo

I built simple Git-based CMS for Hugo static site generators. No backend, no database, no configs. Just login with Github, select your repo and start editing. If you use Hugo for blogging, feel free to check it out at https://github.com/arashthr/hugo-flow > Why did you make it? I wanted to be able to write posts on my phone, and it's not easy to do that with Markdown. Adding images is also always a headache: copy them, minimize and compress them, remember the correct syntax for images, and type the path. > How did you make it? I used Google Stitch for the design and Antigravity for coding. > What about alternatives? Check out Front-end interfaces page in Hugo website. None of them is as simple and dumb as I wanted. > But is it actually working? It's not perfect, but it works well for me. You're welcome to open issues if you find problems.

Visit productView on Hacker NewsMay 20, 2026
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Actual performance

32points
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, coding, open · Missing: mac, agents, macos
87%87% 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 · Missing: https docs, excited, just released
60%60% 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
58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: google, way · Missing: mobile apps, ios, personal
41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive
38%38% 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
21%21% 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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