Clipboard Plus, free and open-source clipboard manager for Windows

Hacker News

Clipboard Plus is a Windows utility to view and manage the Windows clipboard. Download : https://github.com/oormicreations/ClipboardPlus/releases It maintains and can display up to five copied items or clips. Clicking on a clip loads it back into the clipboard and it is ready for pasting into another application. You can clear or save individual clips or all clips by clicking on the corresponding menu items. You can edit the clips and open urls directly from the clipboard plus. The clips can be added to sticky clips, which is like a built in sticky notes with reminders etc. You can enable or disable password mode. When enabled, it masks the copied passwords. You can minimize the Clipboard Plus window to the tray. This tiny but useful utility is completely free and open sourced.

Visit product View on Hacker NewsSep 7, 2018

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Product HuntOn track for Day 1 leaderboard · Strong signals: tiny, notes, open · Missing: mac, agents, macos

65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

45%45% 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: plus · Missing: platform, intuitive, reviews

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

27%27% 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

18%18% 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

12%12% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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