I

I made a file sharing tool that encodes the files within the URL

Hacker News

I made a file sharing tool that encodes the files within the URL

I built this tool to transfer files using just the URL, without storing files on a server. The file is Base64-encoded and embedded as a payload within the URL via the URI fragment (delineated by the # character) which means the file/payload shouldn't get sent to the server. Built mainly for fun, but I have found limited use cases for it (eg. I use a shared mouse/keyboard + clipboard across multiple machines, so use this to transfer files between them; I also have found it useful for file transfers to mobiles - via Edge's URL to QR code feature). It's really only suitable for small file transfers as you might imagine!

Visit product View on Hacker NewsFeb 15, 2025

Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

52%52% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: mac, using, code · Missing: agents, macos, agent

50%50% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

48%48% 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 · Missing: plus, platform, intuitive

41%41% 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

29%29% 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

16%16% 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

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

Correct prediction on native model

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