Audio Transcription + Summarization Skill

What This Skill Enables

Claude can transcribe audio files (MP3, WAV, M4A, etc.) and generate structured summaries with timestamps, action items, and speaker identification. This skill leverages Whisper AI and ffmpeg through Claude's Code Interpreter to process audio locally.

Compatibility

Native

• Claude Code / Claude: native skill usage via SKILL.md.
• Codex/OpenAI workflows: compatible with Agent Skills-style SKILL.md content as reusable workflow instructions.

Manual Adaptation

• Gemini CLI: native skill usage via .gemini/skills/<skill-name>/SKILL.md or .agents/skills/<skill-name>/SKILL.md where supported.
• Cursor: use the generated .cursor/rules/*.mdc adapter for project rules.
• OpenClaw and similar agents: use the same skill content as a reusable prompt/workflow file when native skill import is unavailable.

Prerequisites

Required:

• Claude Pro subscription
• Code Interpreter feature enabled in Claude Desktop settings
• Audio file uploaded to conversation (drag and drop)

What Claude handles automatically:

• Installing and running Whisper AI models
• Audio format conversion with ffmpeg
• Timestamp extraction and alignment
• Summary generation and structuring

How to Use This Skill

Basic Transcription

Prompt: "Transcribe this audio file and give me a clean text transcript."

Claude will:

1. Detect the audio format
2. Convert to optimal format for transcription
3. Run Whisper AI transcription
4. Return formatted text

Timestamped Summary

Prompt: "Transcribe this meeting recording and create a timestamped summary with key discussion points every 5 minutes."

Claude will:

1. Transcribe the full audio
2. Chunk by time intervals
3. Summarize each segment
4. Present with timestamps

Action Items Extraction

Prompt: "Transcribe this audio and extract all action items, decisions, and to-dos mentioned."

Claude will:

1. Transcribe the audio
2. Analyze for actionable items
3. List action items with timestamps
4. Identify who was assigned what (if mentioned)

Speaker Diarization

Prompt: "Transcribe this conversation and identify different speakers. Label them as Speaker 1, Speaker 2, etc."

Claude will:

1. Detect speaker changes in the audio
2. Segment by speaker
3. Label each segment
4. Present as a conversation transcript

Transcription engines compared

This skill defaults to OpenAI Whisper, but you can pair it with hosted APIs when you need streaming or built-in audio intelligence:

Use Whisper for local, no-cost, privacy-preserving transcription; reach for Deepgram for real-time streaming or AssemblyAI when you want higher-level audio analysis out of the box.

Tips for Best Results

1. Audio Quality Matters: Clear audio with minimal background noise produces better transcriptions
2. File Size: For files over 25MB, mention if you want a specific time range transcribed first
3. Language: Specify the language if it's not English (e.g., "Transcribe this Spanish audio...")
4. Model Selection: For better accuracy on difficult audio, ask Claude to use the "medium" or "large" Whisper model
5. Post-Processing: Ask Claude to clean up transcription artifacts like repeated words or filler sounds

Common Workflows

Meeting Minutes Generation

"Transcribe this meeting and create:
1. Attendee list (if mentioned)
2. Key discussion topics with timestamps
3. Decisions made
4. Action items with owners
5. Next steps"

Podcast Summary

"Transcribe this podcast episode and create:
1. Episode summary (2-3 sentences)
2. Main topics discussed with timestamps
3. Key quotes
4. Chapters (every 10 minutes)"

Interview Transcription

"Transcribe this interview with speaker labels.
Format as Q&A with:
- Interviewer questions highlighted
- Interviewee responses
- Notable quotes pulled out"

Troubleshooting

Issue: Transcription is inaccurate Solution: Ask Claude to use a larger Whisper model or pre-process the audio for noise reduction

Issue: Wrong language detected Solution: Explicitly specify the language in your prompt ("Transcribe this French audio...")

Issue: Timestamps are off Solution: Ask Claude to re-align timestamps or specify the desired timestamp interval

Issue: Speaker diarization missing Solution: Request it explicitly: "Please identify different speakers and label them"

Learn More

• Whisper AI by OpenAI - The underlying transcription model
• ffmpeg Audio Processing - Audio format conversion details
• Claude Code Interpreter - How Claude executes code
• Simon Willison's Analysis - Deep dive into Claude's skills

Features

• Local processing via Whisper
• Format conversion with ffmpeg
• Timestamped notes and action items
• Optional speaker labels
• Multilingual support (99 languages with auto-detection)
• Word-level timestamp accuracy
• Multiple output formats (TXT, VTT, SRT, JSON)
• Real-time streaming transcription support with live audio processing, continuous transcription updates, and low-latency transcription for live events or meetings

Use Cases

• Summarize meetings and podcasts
• Generate action items
• Create searchable transcripts
• Generate meeting minutes with action items
• Create accessible transcripts for video content
• Extract insights from podcast episodes

• Source repositorygithub.com 2025-10-15
• Documentationgithub.com
• Package (SHA-256 pinned)/downloads/skills/audio-transcription-summarization.zip