transcribe-video — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited transcribe-video (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Generate subtitles and transcripts from $ARGUMENTS (a video or audio file path, optionally followed by a language code like en-US or es-ES) using AWS Transcribe.
Outputs .srt, .vtt, and .txt files next to the source file.
ffmpeg and aws CLI are installed and configuredffmpeg installed (brew install ffmpeg)aws CLI installed and configured with valid credentials (brew install awscli && aws configure)s3:* (create/delete buckets), transcribe:* (start/delete jobs)ffmpeg -i "input.mp4" -vn -acodec mp3 -q:a 2 "/tmp/transcribe-audio.mp3" -yBUCKET="tmp-transcribe-$(date +%s)"
aws s3 mb "s3://$BUCKET" --region us-east-1
aws s3 cp "/tmp/transcribe-audio.mp3" "s3://$BUCKET/audio.mp3"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-1Language 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.
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
doneSave .srt and .vtt next to the original file:
aws s3 cp "s3://$BUCKET/$JOB_NAME.srt" "/path/to/input.srt"
aws s3 cp "s3://$BUCKET/$JOB_NAME.vtt" "/path/to/input.vtt"Download the JSON result and extract the full transcript text:
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.
IMPORTANT: Always clean up to avoid recurring S3 storage costs.
# 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"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+ |
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)ls -lh /path/to/original-video.{srt,vtt,txt}~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.