Timestampconverter.net – Auto-detecting timestamp converter

Hacker News

I got tired of timestamp converters that make you click through dropdowns to select formats or are buried in ads, so I built one that auto-detects the input and shows all formats at once. Just paste any timestamp: Unix (seconds/ms), ISO 8601, RFC 2822, whatever, and it instantly converts to 7 common formats with one-click copy. No dropdowns, no ads, no tracking. Features: Auto-detection of input format 400+ timezone support with search Date math (add/subtract time units) Duration calculator between two timestamps Bulk conversion (paste multiple, convert all) URL parameters for sharing (?ts=1706745600) Dark mode default Tech: Pure vanilla JS + day.js (~50KB total), hosted on Cloudflare Pages for free. I use it daily when debugging API logs or working with different timezone databases. Built it over a weekend to scratch my own itch. Live: https://timestampconverter.net

Visit product View on Hacker NewsJan 31, 2026

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best fitHighest predicted score across all platforms for this description.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

39%39% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive

29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: para · Missing: mobile apps, ios, personal

27%27% 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

22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

18%18% predicted probability of success on Product Hunt, 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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