agentleFS
aiagentwithdhruvaiagentwithdhruv/skills/whisper-voice/SKILL.md

whisper-voice

Skill16 starsChanged 9 months agoMITView on GitHub

Native macOS menu bar app for live voice-to-text with auto-type using WhisperKit on Apple Silicon

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Wait for model download (~140MB for base model)

    line 36
  2. Distinctive:

    No API keys needed (fully offline)

    line 62

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Whisper Voice — Live Speech-to-Text Mac App

Goal

Build and run a native macOS menu bar app that captures live microphone audio, transcribes it offline using WhisperKit (on Apple Silicon), and auto-types the text wherever the cursor is.

Inputs

NameTypeRequiredDescription
model_sizestringNoWhisper model: tiny, base (default), small
languagestringNo"en" (default) or "hi" for Hindi mode
chunk_durationfloatNoSeconds per audio chunk (default: 3.0)

Process

1. Build the app

cd AiwithDhruv_Voice/WhisperAiwithDhruv
swift build

2. Run the app

swift run WhisperAiwithDhruv
# Or open in Xcode: open Package.swift → Cmd+R

3. First launch setup

  1. Grant microphone permission when prompted
  2. Grant Accessibility in System Settings → Privacy → Accessibility
  3. Wait for model download (~140MB for base model)

4. Usage

  • Cmd+Shift+Space — Toggle recording on/off
  • Click mic icon in menu bar for controls
  • Speak — text auto-types at cursor position
  • Toggle Hindi mode for Hindi/Hinglish input

Outputs

NameTypeDescription
transcribed_textstringLive transcribed text typed at cursor
historyarrayLast 50 transcription entries in menu bar

Edge Cases

  • No mic: Shows error in menu bar dropdown
  • Accessibility denied: Auto-type disabled, manual copy from history
  • Silence: VAD skips silent chunks (energy-based threshold)
  • Hallucinations: Filters common Whisper artifacts ("Thank you.", "...")
  • Model not downloaded: Shows download progress bar

Environment

  • macOS 14+ (Sonoma)
  • Apple Silicon (M1/M2/M3/M4)
  • Xcode 15+ (for building)
  • No API keys needed (fully offline)

Schema

Inputs

NameTypeRequiredDescription
model_sizestringNotiny / base / small
languagestringNoen / hi
chunk_durationfloatNo2.0 - 8.0 seconds
silence_thresholdfloatNo0.002 - 0.05

Outputs

NameTypeDescription
transcriptionstringLive text output
auto_typedbooleanWhether text was injected at cursor

Credentials

NameSource
NoneFully offline, no API keys

Composable With

video-edit (add transcription captions), send-telegram (send transcriptions to phone)

Cost

Free — runs entirely on-device. Model download is one-time (~140MB for base).

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.