whisper-transcription
Transcribe audio and video files to text using OpenAI Whisper. Use when: converting podcasts to blog posts; creating video subtitles; extracting quotes from interviews; repurposing video content to text; building searchable audio archives
- Installs
- 944
- Last 24h
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- Trending rank
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- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/guia-matthieu/clawfu-skills --skill whisper-transcription- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads whisper-transcription automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Whisper Transcription
Transcribe any audio or video to text using OpenAI's Whisper model - the same technology powering ChatGPT voice features.
When to Use This Skill
- Podcast repurposing - Convert episodes to blog posts, show notes, social snippets
- Video subtitles - Generate SRT/VTT files for YouTube, social media
- Interview extraction - Pull quotes and insights from recorded calls
- Content audit - Make audio/video libraries searchable
- Translation - Transcribe and translate foreign language content
What Claude Does vs What You Decide
| Claude Does | You Decide |
|---|---|
| Structures production workflow | Final creative direction |
| Suggests technical approaches | Equipment and tool choices |
| Creates templates and checklists | Quality standards |
| Identifies best practices | Brand/voice decisions |
| Generates script outlines | Final script approval |
Dependencies
pip install openai-whisper torch ffmpeg-python click
# Also requires ffmpeg installed on system
# macOS: brew install ffmpeg
# Ubuntu: sudo apt install ffmpeg
Commands
Transcribe Single File
python scripts/main.py transcribe audio.mp3 --model medium --output transcript.txt
python scripts/main.py transcribe video.mp4 --format srt --output subtitles.srt
Batch Transcription
python scripts/main.py batch ./recordings/ --format txt --output ./transcripts/
Transcribe + Translate
python scripts/main.py translate foreign-audio.mp3 --to en
Extract Timestamps
python scripts/main.py timestamps podcast.mp3 --format json
Examples
Example 1: Podcast to Blog Post
# Transcribe 1-hour podcast
python scripts/main.py transcribe episode-42.mp3 --model medium
# Output: episode-42.txt (full transcript with timestamps)
# Processing time: ~5 min for 1 hour audio on M1 Mac
Example 2: YouTube Subtitles
# Generate SRT for video upload
python scripts/main.py transcribe marketing-video.mp4 --format srt
# Output: marketing-video.srt
# Upload directly to YouTube/Vimeo
Example 3: Batch Process Interview Library
# Transcribe all recordings in folder
python scripts/main.py batch ./customer-interviews/ --model small --format txt
# Output: ./customer-interviews/*.txt (one per audio file)
Model Selection Guide
| Model | Speed | Accuracy | VRAM | Best For |
|---|---|---|---|---|
tiny | Fastest | ~70% | 1GB | Quick drafts, short clips |
base | Fast | ~80% | 1GB | Social media clips |
small | Medium | ~85% | 2GB | Podcasts, interviews |
medium | Slow | ~90% | 5GB | Professional transcripts |
large | Slowest | ~95% | 10GB | Critical accuracy needs |
Recommendation: Start with small for most marketing content. Use medium for client deliverables.
Output Formats
| Format | Extension | Use Case |
|---|---|---|
txt | .txt | Blog posts, analysis |
srt | .srt | Video subtitles (YouTube) |
vtt | .vtt | Web video subtitles |
json | .json | Programmatic access |
tsv | .tsv | Spreadsheet analysis |
Performance Tips
- GPU acceleration - 10x faster with CUDA GPU
- Audio extraction - Script auto-extracts audio from video
- Chunking - Long files auto-split for memory efficiency
- Language detection - Automatic, or specify with
--language
Skill Boundaries
What This Skill Does Well
- Structuring audio production workflows
- Providing technical guidance
- Creating quality checklists
- Suggesting creative approaches
What This Skill Cannot Do
- Replace audio engineering expertise
- Make subjective creative decisions
- Access or edit audio files directly
- Guarantee commercial success
Related Skills
- video-processing - Extract audio from video
- youtube-downloader - Download videos to transcribe
- content-repurposer - Transform transcripts to content
- podcast-production - Create podcasts
Skill Metadata
- Mode: cyborg
category: automation
subcategory: audio-processing
dependencies: [openai-whisper, torch, ffmpeg-python]
difficulty: beginner
time_saved: 10+ hours/week
FAQ
What does the whisper-transcription skill do?
Transcribe audio and video files to text using OpenAI Whisper. Use when: converting podcasts to blog posts; creating video subtitles; extracting quotes from interviews; repurposing video content to text; building searchable audio archives
How do I install whisper-transcription?
Run npx skills add https://github.com/guia-matthieu/clawfu-skills --skill whisper-transcription in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/whisper-transcription/ (personal) or .claude/skills/whisper-transcription/ (project).
Which AI agents can use whisper-transcription?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is whisper-transcription safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains whisper-transcription?
It is published by guia-matthieu in guia-matthieu/clawfu-skills. It has 944 recorded installs.
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