Telltail – Universal Clipboard for Text

Hacker News

Hi folks! Telltail [1] lets you share clipboard between your devices. If you've used or ever known about Apple's Universal Clipboard, it is quite like that. It uses Tailscale [2] to achieve this. I must tell you that setting it up requires you to have some familiarity with the terminal (which already comes installed on your computer). I've written a blog post on how I came about working on it and the iterative process that went behind it. You can read the post here [3]. The instructions to install Telltail can be found here [4]. It is a personal project of mine and is not affiliated to or promoted by any org. Hopefully with discussions and contributions we could add support for more OSs. [1]: https://github.com/ajitid/telltail-center [2]: https://tailscale.com [3]: https://hemarkable.com/prose/telltail [4]: https://guide-on.gitbook.io/telltail

Visit product View on Hacker NewsMar 30, 2023

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

76%76% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntOn track for Day 1 leaderboard · Strong signals: apple, computer · Missing: mac, agents, macos

54%54% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

14%14% 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.

Incorrect prediction on native model

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