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DataXLator – Client-Side JSON ↔ YAML Converter (Privacy-First)

Hacker News

DataXLator – Client-Side JSON ↔ YAML Converter (Privacy-First)

Hi HN, I'm launching DataXLator, a utility I built to solve a problem many of us face: needing quick, reliable conversion between JSON and YAML for config files (Kubernetes, Ansible, etc.) without trusting a random server with sensitive data. The core feature is that all free conversions run 100% client-side in your browser using js-yaml and browser APIs. This guarantees privacy and speed. I've also implemented real-time error reporting to help debug syntax issues instantly. While the core tool is FREE, I'm launching with a Pro subscription to fund development of high-value, server-backed features like Bulk ZIP Conversion and support for formats like CSV and SQL. I would genuinely appreciate any feedback on the tool's performance and what features are most critical to your workflow.

Visit productView on Hacker NewsSep 29, 2025
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AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
42%42% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: using, apis · Missing: mac, agents, macos
35%35% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
25%25% 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 · Missing: mobile apps, ios, personal
19%19% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: subscription · 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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