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Pastehub.app – 100 % client-side toolbox for whatever you just copied

Hacker News

Pastehub.app – 100 % client-side toolbox for whatever you just copied

I kept opening 10+ tabs for the same daily clipboard chores, so I crammed a bunch of tiny client-side tools into one page: Drop any image → OCR + dominant color palette + QR/barcode decode Paste “72 kg in pounds”, “50C to F”, “180 cm to feet” → instant conversion Paste any math expression → instant result JSON pretty/minify, JWT decode, Base64 → text/file, hex, URL tracking-strip, etc. All 100 % in-browser, zero backend, nothing ever leaves your machine It’s deliberately over-engineered for the weird stuff I copy every day. Try throwing something at it and tell me what breaks or what’s missing. Feedback button goes straight to me. https://pastehub.app

Visit product View on Hacker NewsNov 25, 2025

Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

55%55% 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 HuntUnlikely to reach the leaderboard · Strong signals: mac, tiny, code · Missing: agents, macos, agent

47%47% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

46%46% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

28%28% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

25%25% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

24%24% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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