Another Voice dictation and voice-to-prompt for macOS

Hacker News

WhisperShortcut is a macOS menu bar app for voice dictation and voice-to-prompt across your system. I built this after paying monthly for a transcription app and wanting Cursor's voice-to-prompt feature everywhere. Press a shortcut, speak, get text in clipboard. Works in emails, Slack, Teams, code editors—anywhere. Three modes: Transcription: Shortcut → speak → text in clipboard. Uses Gemini Flash for speed (lowest latency). Whisper available for offline. Voice-to-Prompt: Select text, press shortcut, speak instruction. Gemini processes selected text + voice instruction. Result goes to clipboard. Like Cursor's prompt-on-selection, but system-wide. Read Aloud: Select text, press shortcut, speak command (or stay silent). If command: applies prompt first, then reads result. If no command: reads selected text directly. Use cases: dictating prompts in Cursor, formatting messages, summarizing articles. Native Swift/Cocoa app. Open source. Daily driver for me. https://github.com/mgsgde/whisper-shortcut Demo: https://youtu.be/yz8cbaI6NYQ .

Visit product View on Hacker NewsDec 25, 2025

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, cursor · Missing: agents, agent, claude

97%97% 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.

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

73%73% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

50%50% 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.

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

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

nativeThis product was originally launched on this platform.

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

26%26% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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