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transcribe-video — Claude Code skill for video transcripts

Creates subtitle files and plain-text transcripts from audio or video with AWS Transcribe. Use it to caption clips or make spoken content searchable.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add rameerez/claude-code-startup-skills --skill transcribe-video -a claude-code
Open on GitHub

What transcribe-video does

The skill extracts audio from a video with ffmpeg, uploads it to a temporary S3 bucket, then starts an AWS Transcribe job. It saves .srt and .vtt subtitles beside the original file, along with a .txt transcript without timestamps.

You need ffmpeg and a configured aws CLI with credentials that allow s3:* and transcribe:* operations. After transcription, the skill removes the bucket, the Transcribe job, and temporary files. If cleanup does not finish, objects left in S3 can continue to use storage and incur charges.

What it helps with

  • create .srt and .vtt subtitles from a video
  • turn an audio recording into a text transcript
  • pull spoken words from a video for notes
  • make video content searchable by transcript

Example prompts for the agent

  • Create subtitles and a transcript for meeting.mp4.
  • Transcribe interview.mp3 in es-ES.
  • Generate .srt, .vtt, and .txt files for demo.mp4.

How to install transcribe-video

1Skills CLI (Vercel)

npx skills add rameerez/claude-code-startup-skills --skill transcribe-video -a claude-code

2Manually: put the files in place

~/.claude/skills/transcribe-video/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/transcribe-video/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about transcribe-video

How do I install transcribe-video in Claude Code?

Run npx skills add rameerez/claude-code-startup-skills --skill transcribe-video -a claude-code. The skill file is placed at ~/.claude/skills/transcribe-video/SKILL.md.

What does transcribe-video do?

It sends audio from a video or audio file to AWS Transcribe and produces .srt and .vtt subtitles plus a plain-text .txt transcript.

What does transcribe-video need to run?

You need ffmpeg and a configured aws CLI. The AWS credentials must allow s3:* and transcribe:* operations.

Source text

SKILL.md · MIT
---
name: transcribe-video
description: Generate subtitles (SRT/VTT) and plain text transcripts from video or audio files using AWS Transcribe. Use when creating captions, extracting spoken content, generating transcripts for notes, or making video content searchable.
argument-hint: "[file] [language-code]"
allowed-tools: Bash(ffmpeg:*), Bash(aws:*), Bash(ls:*), Bash(rm:*), Bash(which:*)
---

# Video Transcription Skill

Generate subtitles and transcripts from `$ARGUMENTS` (a video or audio file path, optionally followed by a language code like `en-US` or `es-ES`) using AWS Transcribe.

Outputs `.srt`, `.vtt`, and `.txt` files next to the source file.

## Process

1. **Verify prerequisites** - check `ffmpeg` and `aws` CLI are installed and configured
2. **Extract audio** from the video as MP3 using ffmpeg
3. **Create temporary S3 bucket**, upload audio
4. **Run AWS Transcribe** job with SRT and VTT subtitle output
5. **Download results** and generate plain text transcript
6. **Clean up all AWS resources** - delete S3 bucket, Transcribe job, and temp files. No recurring costs.

## Prerequisites

- `ffmpeg` installed (`brew install ffmpeg`)
- `aws` CLI installed and configured with valid credentials (`brew install awscli && aws configure`)
- AWS credentials need permissions for: `s3:*` (create/delete buckets), `transcribe:*` (start/delete jobs)

## Step-by-Step

### Step 1: Extract audio

```bash
ffmpeg -i "input.mp4" -vn -acodec mp3 -q:a 2 "/tmp/transcribe-audio.mp3" -y
```

### Step 2: Create temp S3 bucket and upload

```bash
BUCKET="tmp-transcribe-$(date +%s)"
aws s3 mb "s3://$BUCKET" --region us-east-1
aws s3 cp "/tmp/transcribe-audio.mp3" "s3://$BUCKET/audio.mp3"
```

### Step 3: Start transcription job

```bash
JOB_NAME="tmp-job-$(date +%s)"
aws transcribe start-transcription-job \
  --transcription-job-name "$JOB_NAME" \
  --language-code en-US \
  --media-format mp3 \
  --media "MediaFileUri=s3://$BUCKET/audio.mp3" \
  --subtitles "Formats=srt,vtt" \
  --output-bucket-name "$BUCKET" \
  --region us-east-1
```

**Language codes:** `en-US`, `es-ES`, `fr-FR`, `de-DE`, `pt-BR`, `ja-JP`, `zh-CN`, `it-IT`, `ko-KR`, etc. Default to `en-US` if not specified.

### Step 4: Poll until complete

```bash
while true; do
  STATUS=$(aws transcribe get-transcription-job \
    --transcription-job-name "$JOB_NAME" \
    --region us-east-1 \
    --query 'TranscriptionJob.TranscriptionJobStatus' \
    --output text)
  if [ "$STATUS" = "COMPLETED" ] || [ "$STATUS" = "FAILED" ]; then break; fi
  sleep 5
done
```

### Step 5: Download subtitle files

Save `.srt` and `.vtt` next to the original file:

```bash
aws s3 cp "s3://$BUCKET/$JOB_NAME.srt" "/path/to/input.srt"
aws s3 cp "s3://$BUCKET/$JOB_NAME.vtt" "/path/to/input.vtt"
```

### Step 6: Generate plain text transcript

Download the JSON result and extract the full transcript text:

```bash
aws s3 cp "s3://$BUCKET/$JOB_NAME.json" "/tmp/transcribe-result.json"
```

Then use a tool to extract the `.results.transcripts[0].transcript` field from the JSON and save it as a `.txt` file next to the original.

### Step 7: Clean up everything

**IMPORTANT:** Always clean up to avoid recurring S3 storage costs.

```bash
# Delete S3 bucket and all contents
aws s3 rb "s3://$BUCKET" --force --region us-east-1

# Delete the transcription job
aws transcribe delete-transcription-job --transcription-job-name "$JOB_NAME" --region us-east-1

# Delete temp audio file
rm -f "/tmp/transcribe-audio.mp3" "/tmp/transcribe-result.json"
```

## Real-World Results (Reference)

From actual transcription runs:

| Video | Duration | Audio Size | Transcribe Time | Subtitle Segments |
|-------|----------|------------|-----------------|-------------------|
| X/Twitter clip | 2:40 | 2.5 MB | ~20 seconds | 83 |
| Screen recording | 18:45 | 11.4 MB | ~60 seconds | 500+ |

### Key Insights

1. **AWS Transcribe is fast** - even 19-minute videos complete in about a minute
2. **Short-form content** (tweets, reels) transcribes almost instantly
3. **Cost is negligible** - AWS Transcribe charges ~$0.024/min, so a 19-min video costs ~$0.46
4. **Cleanup is critical** - always delete the S3 bucket to avoid storage charges
5. **SRT is most compatible** - works with most video players and editors; VTT is better for web

## Output Files

```
original-video.mp4
original-video.srt          # Subtitles with timestamps (most compatible)
original-video.vtt          # Web-optimized subtitles (for HTML5 <track>)
original-video.txt          # Plain text transcript (no timestamps)
```

## After Transcription

1. **Verify all output files exist**: `ls -lh /path/to/original-video.{srt,vtt,txt}`
2. Report the number of subtitle segments and total duration
3. Confirm all AWS resources have been cleaned up (no S3 buckets, no Transcribe jobs remaining)

© rameerez · MIT · rameerez/claude-code-startup-skills

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