Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Transcribe audio files to text using local Whisper (Docker). Use when receiving voice messages, audio files (.mp3, .m4a, .ogg, .wav, .webm), or when asked to transcribe audio content.
Transcribe audio files to text using local Whisper (Docker). Use when receiving voice messages, audio files (.mp3, .m4a, .ogg, .wav, .webm), or when asked to transcribe audio content.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Local audio transcription using faster-whisper in Docker.
cd /path/to/skills/transcribe/scripts chmod +x install.sh ./install.sh This builds the Docker image whisper:local and installs the transcribe CLI.
transcribe /path/to/audio.mp3 [language] Default language: es (Spanish) Use auto for auto-detection Outputs plain text to stdout
transcribe /tmp/voice.ogg # Spanish (default) transcribe /tmp/meeting.mp3 en # English transcribe /tmp/audio.m4a auto # Auto-detect
mp3, m4a, ogg, wav, webm, flac, aac
Save the audio attachment to a temp file Run transcribe <path> Include the transcription in your response Clean up the temp file
scripts/transcribe - CLI wrapper (bash) scripts/install.sh - Installation script (includes Dockerfile inline)
Model: small (fast) - edit install.sh for large-v3 (accurate) Fully local, no API key needed
Messaging, meetings, inboxes, CRM, and teammate communication surfaces.
Largest current source with strong distribution and engagement signals.