transcribe-audio_skill

Overview

This skill transcribes video audio with WhisperX and produces JSON transcripts that preserve original video timestamps. It generates word-level timing and includes the video source path as metadata. Use it when you need accurate, timeline-aligned transcripts for downstream analysis.

How this skill works

The skill runs WhisperX directly on video files (do not extract audio) so timestamps align with the original video timeline, including leading silence. After WhisperX completes, a Ruby preparation script cleans and prettifies the JSON, removes unnecessary fields, and injects video source metadata. The skill returns a concise success response pointing to the transcript path and original video file.

When to use it

• You need accurate, timeline-aligned transcripts for videos before visual analysis.
• You require word-level timing for subtitle generation or search indexing.
• You must preserve original video timestamps including leading silence.
• You plan to run many transcriptions in parallel inside task agents.
• You want clean, compact JSON transcripts with source metadata included.

Best practices

• Run WhisperX directly on video files; do not extract audio separately to avoid timestamp drift.
• Read the library language code from the library metadata file and pass it to WhisperX.
• Use the prepare script after WhisperX to remove extra fields and add video path metadata for traceability.
• Run one video per task agent to enable safe parallel execution and avoid race conditions.
• Do not update the library metadata file from this skill; let the parent agent handle library-level updates.

Example use cases

• Generate searchable, timestamped transcripts for a video archive before running visual content analysis.
• Produce word-accurate subtitles for training machine learning models that require aligned text/audio pairs.
• Create JSON transcripts with per-word timing for indexing and video search features.
• Run many simultaneous transcriptions across a media library using task agents, then hand results to a parent agent for cataloging.
• Preprocess videos for a pipeline that combines audio transcripts with visual scene descriptions from a separate analysis skill.