How do I install the Transcribe Audio skill?

Run npx skillmds@latest add majiayu000/transcribe-audio in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Transcribe Audio safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Transcribe Audio?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Transcribe Audio free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Transcribe Audio?

majiayu000 (@majiayu000) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Transcribe Audio by majiayu000 — Agent Skill

Name: Transcribe Audio
Rating: 4.2 (5 reviews)
Author: majiayu000

File contents

Skill: Transcribe Audio

Transcribes video audio using WhisperX and creates clean JSON transcripts with word-level timing data.

When to Use

Videos need audio transcripts before visual analysis

Critical Requirements

Use WhisperX, NOT standard Whisper. WhisperX preserves the original video timeline including leading silence, ensuring transcripts match actual video timestamps. Run WhisperX directly on video files. Don't extract audio separately - this ensures timestamp alignment.

Workflow

1. Read Language from Library File

Read the library's library.yaml to get the language code:

# Library metadata
library_name: [library-name]
language: en  # Language code stored here
...

2. Run WhisperX

whisperx "/full/path/to/video.mov" \
  --language en \
  --model medium \
  --compute_type float32 \
  --device cpu \
  --output_format json \
  --output_dir libraries/[library-name]/transcripts

3. Prepare Audio Transcript

After WhisperX completes, format the JSON using our prepare_audio_script:

ruby .claude/skills/transcribe-audio/prepare_audio_script.rb \
  libraries/[library-name]/transcripts/video_name.json \
  /full/path/to/original/video_name.mov

This script:

Adds video source path as metadata
Removes unnecessary fields to reduce file size
Prettifies JSON

4. Return Success Response

After audio preparation completes, return this structured response to the parent agent:

✓ [video_filename.mov] transcribed successfully
  Audio transcript: libraries/[library-name]/transcripts/video_name.json
  Video path: /full/path/to/video_filename.mov

DO NOT update library.yaml - the parent agent will handle this to avoid race conditions when running multiple transcriptions in parallel.

Running in Parallel

This skill is designed to run inside a Task agent for parallel execution:

Each agent handles ONE video file
Multiple agents can run simultaneously
Parent thread updates library.yaml sequentially after each agent completes
No race conditions on shared YAML file

Next Step

After audio transcription, use the analyze-video skill to add visual descriptions and create the visual transcript.

Installation

Ensure WhisperX is installed. Use the setup skill to verify dependencies.

---name: transcribe-audiodescription: Transcribes video audio using WhisperX, preserving original timestamps. Creates JSON transcript with word-level timing. Use when you need to generate audio transcripts for videos.--- # Skill: Transcribe Audio Transcribes video audio using WhisperX and creates clean JSON transcripts with word-level timing data. ## When to Use - Videos need audio transcripts before visual analysis ## Critical Requirements Use WhisperX, NOT standard Whisper. WhisperX preserves the original video timeline including leading silence, ensuring transcripts match actual video timestamps. Run WhisperX directly on video files. Don't extract audio separately - this ensures timestamp alignment. ## Workflow ### 1. Read Language from Library File Read the library's `library.yaml` to get the language code: ```yaml # Library metadata library_name: [library-name] language: en # Language code stored here ... ``` ### 2. Run WhisperX ```bash whisperx "/full/path/to/video.mov" \ --language en \ --model medium \ --compute_type float32 \ --device cpu \ --output_format json \ --output_dir libraries/[library-name]/transcripts ``` ### 3. Prepare Audio Transcript After WhisperX completes, format the JSON using our prepare_audio_script: ```bash ruby .claude/skills/transcribe-audio/prepare_audio_script.rb \ libraries/[library-name]/transcripts/video_name.json \ /full/path/to/original/video_name.mov ``` This script: - Adds video source path as metadata - Removes unnecessary fields to reduce file size - Prettifies JSON ### 4. Return Success Response After audio preparation completes, return this structured response to the parent agent: ``` ✓ [video_filename.mov] transcribed successfully Audio transcript: libraries/[library-name]/transcripts/video_name.json Video path: /full/path/to/video_filename.mov ``` **DO NOT update library.yaml** - the parent agent will handle this to avoid race conditions when running multiple transcriptions in parallel. ## Running in Parallel This skill is designed to run inside a Task agent for parallel execution: - Each agent handles ONE video file - Multiple agents can run simultaneously - Parent thread updates library.yaml sequentially after each agent completes - No race conditions on shared YAML file ## Next Step After audio transcription, use the **analyze-video** skill to add visual descriptions and create the visual transcript. ## Installation Ensure WhisperX is installed. Use the **setup** skill to verify dependencies.

Frequently asked questions

Transcribe Audio