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transcribe-video转录视频

Agent Skill

用于辅助视频生成、动画合成、脚本化剪辑或 Remotion 等视频项目开发。它适合让 Agent 组织镜头、生成素材说明、维护合成代码或排查渲染问题。使用时需要确认分辨率、时长、素材路径和导出格式;涉及外部素材、人物肖像或商业发布时,应先核对版权授权和内容审核要求。

总安装

1,297

周安装

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下载量

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CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:transcribe-video(转录视频)
来源仓库:https://github.com/rameerez/claude-code-startup-skills
仓库路径:skills/transcribe-video
安装命令:
npx skills add https://github.com/rameerez/claude-code-startup-skills --skill transcribe-video
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/rameerez/claude-code-startup-skills --skill transcribe-video

简介

用于辅助视频转录、字幕生成或语音转文本处理。

  • 适合从音频文件中提取文字内容并格式化输出。
  • 可结合时间戳对齐对话段落,便于后续编辑。
  • 需确认音频质量、语言和说话人数量。transcribe-video 属于开发类 Skill,可作为该场景下的辅助能力补充。
  • 涉及版权素材时应先获得合法授权再进行处理。

SKILL.md

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

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

Step 2: Create temp S3 bucket and upload

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

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

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:

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:

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.

# 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:

VideoDurationAudio SizeTranscribe TimeSubtitle Segments
X/Twitter clip2:402.5 MB~20 seconds83
Screen recording18:4511.4 MB~60 seconds500+

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)

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

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能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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