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A Simple, Ad-Free, Privacy-Respecting JSON Linter

Hacker News

A Simple, Ad-Free, Privacy-Respecting JSON Linter

I built this JSON linter because, while there are plenty of great ones out there, I wanted something that fits my needs—ad-free, no tracking, privacy-focused, and lightweight. What started as a quick “1-hour project” quickly spiraled into a more "complex" challenge. Initially, I used a simple <textarea>. It was easy, fast, and functional, but I wanted code highlighting for better readability. That’s when things got tricky. Implementing syntax highlighting meant moving to a <div> with contenteditable. While it works, it introduced issues like cursor jumping during formatting—one of those things that seems simple but can be maddening in practice. Looking back, the better approach would’ve been to stick with a <textarea> for editing and use a separate <div> for displaying formatted, syntax-highlighted JSON. Lesson learned. Right now, it works (though it’s not perfect), and I’m sure there are some rough edges in the editing experience. Still, it "works" and I plan to keep improving it over time. My next planned feature is adding JSON Query functionality, which should make it more versatile. Honestly, I’m probably posting this just to hear comments like, “What’s the most useless thing you’ve ever built?” But hey, if you try it out, break it, or even like it, let me know!

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: cursor, code · Missing: mac, agents, macos
76%76% 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 · Strong signals: started, para · Missing: supports, reddit linkedin, podcasting
74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
59%59% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
51%51% 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
35%35% 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
12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: introduce · 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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