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transcribe-video

Generate subtitles (SRT/VTT) and plain text transcripts from video or audio files using AWS Transcribe.

Skill by rameerez

IndexedMIT★ 31
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

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About

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.

Use cases: cloud, writing, productivity

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/transcribe-video

Tools it pre-approves 5

From allowed-tools in SKILL.md: the agent may use these without asking you each time.

  • Bash(ffmpeg:*),
  • Bash(aws:*),
  • Bash(ls:*),
  • Bash(rm:*),
  • Bash(which:*)

What's inside

Skill 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.
License
MIT
Allowed tools
Bash(ffmpeg:*),, Bash(aws:*),, Bash(ls:*),, Bash(rm:*),, Bash(which:*)
Instructions
134 lines in SKILL.md · view on GitHub

Before installing

  • Pre-approves some shell commands

Files (1)

  • SKILL.md

SKILL.md (first lines)

# 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

From rameerez/claude-code-startup-skills, MIT.

Signals

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Last commit (this folder)
Feb 5, 2026 (8 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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Cite this page

transcribe-video skill. Agent Mart. https://agentmart.dev/skills/rameerez-transcribe-video (last updated 2026-10-24)