youtube-kr-subtitle

name	youtube-kr-subtitle
description	Download YouTube videos, extract English subtitles, translate them to Korean using Claude's own translation capabilities (with video context and web search), and burn Korean subtitles into the video. Use this skill when the user requests Korean subtitle insertion for YouTube videos or asks to translate YouTube content to Korean.

YouTube Korean Subtitle Translator

Overview

This skill enables Claude to download YouTube videos and create new versions with Korean subtitles burned directly into the video. Unlike traditional approaches that use Google Translate, this skill leverages Claude's own translation capabilities with full context awareness - including video metadata, web research about the content, and understanding of the subject matter.

When to Use This Skill

Use this skill when users request:

• "Add Korean subtitles to this YouTube video: [URL]"
• "Translate this YouTube video to Korean"
• "Download this video and burn Korean subtitles into it"
• "Create a Korean version of this YouTube video"

Workflow

Step 0: Environment Setup Check (First Time Only)

Before processing any videos, verify that the environment is properly configured:

python scripts/setup_check.py

This script checks:

• Python version (3.7+)
• Virtual environment existence
• Required packages (yt-dlp, pysrt, ffmpeg-python, deep-translator)
• FFmpeg installation

Auto-fix mode: To automatically create venv and install packages:

python scripts/setup_check.py --auto-fix

Output: JSON containing:

• success: boolean indicating if all checks passed
• results: detailed information about each component
• actions_taken: list of automatic fixes performed (if --auto-fix used)

What the script does in auto-fix mode:

1. Creates virtual environment if it doesn't exist
2. Installs all required Python packages from requirements.txt
3. Verifies FFmpeg is installed (provides installation instructions if not)

Error Handling: If FFmpeg is not installed, the script will provide platform-specific installation commands. FFmpeg cannot be auto-installed and must be installed manually.

Important: Run this check before your first video processing. Once the environment is set up, you don't need to run this again unless you encounter dependency issues.

Step 1: Download Video and Subtitles

Run the download script to fetch the YouTube video, English subtitles, and metadata:

python scripts/download_youtube.py "<youtube_url>" downloads/

Output: JSON containing:

• video_path: Downloaded video file path
• subtitle_path: English subtitle SRT file path (or null if not available)
• title: Video title
• description: Video description
• duration: Video duration in seconds
• video_id: YouTube video ID

Error Handling: If subtitle_path is null, inform the user that the video lacks English subtitles and cannot be processed in the current version.

Step 2: Extract Subtitle Text

Extract only the text content from the SRT file for translation:

python scripts/extract_subtitle_text.py <subtitle_path>

Output: JSON containing:

• texts: Array of subtitle text strings (preprocessed and grouped into sentences)
• metadata.total_count: Number of subtitle entries
• metadata.processed_count: Number after preprocessing (overlap fixes, grouping)

Important: The script automatically:

• Fixes overlapping timestamps (YouTube's rolling caption format)
• Removes short duplicate subtitles (<150ms)
• Groups consecutive subtitles into sentence units for better translation context

Step 3: Gather Context for Translation

Before translating, build comprehensive context to ensure high-quality, contextually-aware translation:

3a. Analyze Video Metadata

Review the video title and description from Step 1. Identify:

• Subject matter (technology, education, entertainment, etc.)
• Key topics or themes
• Technical terminology that may require specialized translation
• Tone and style (formal, casual, educational, etc.)

3b. Web Search for Additional Context

Perform web searches to understand the content better:

Search queries to consider:
- "[video_title]" - Find related content and context
- "[key_topics] Korean translation" - Find established Korean terminology
- "[subject_matter] 한글 용어" - Find domain-specific Korean terms

Save findings to a context file for reference during translation.

3c. Create Translation Context File

Write a context file (e.g., downloads/video_context.md) containing:

# Translation Context for [Video Title]

## Video Overview
- **Title:** [title]
- **Subject:** [subject matter]
- **Duration:** [duration]
- **Key Topics:** [list of main topics]

## Key Terminology
[Table of English terms and their appropriate Korean translations]

## Tone and Style
[Description of the appropriate translation style]

## Additional Notes
[Any web research findings, cultural considerations, or translation guidelines]

Step 4: Translate Subtitles with Claude

Now perform the actual translation using the context gathered above. This is where Claude's capabilities shine:

Translation Guidelines:

1. Read the context file created in Step 3c
2. Review the first few subtitle texts to understand the flow
3. Translate each subtitle text to Korean, considering:
   • Context awareness: Use video metadata and web research findings
   • Terminology consistency: Apply terms from the context file
   • Sentence flow: Maintain natural Korean sentence structure
   • Cultural adaptation: Adapt idioms and cultural references appropriately
   • Length consideration: Keep translations reasonably similar in length to fit subtitle timing
4. Maintain the exact same number of entries as the input array

Output Format: Create a JSON array of translated strings and save it:

[
  "첫 번째 번역된 자막",
  "두 번째 번역된 자막",
  "세 번째 번역된 자막"
]

Save this to a file like downloads/translated_texts.json.

Quality Checks:

• Verify the array length matches the original subtitle count
• Ensure no entries are empty (unless the original was empty)
• Check that technical terms are consistently translated
• Confirm the tone matches the video's style

Step 5: Merge Translated Text with SRT Timestamps

Combine the translated texts with the original SRT timing information:

python scripts/merge_translated_subtitle.py <original_srt> <translated_json> <output_srt>

Example:

python scripts/merge_translated_subtitle.py \
  downloads/video.en.srt \
  downloads/translated_texts.json \
  downloads/video.ko.srt

Output: JSON containing:

• success: boolean
• subtitle_count: number of subtitles processed
• output_path: path to Korean SRT file

Step 6: Burn Subtitles into Video

Use FFmpeg to hardcode the Korean subtitles into the video:

python scripts/process_video.py <video_path> <korean_srt> <output_path> [font_name] [font_size]

Example:

python scripts/process_video.py \
  downloads/video.mp4 \
  downloads/video.ko.srt \
  output/video_korean.mp4 \
  Arial 24

Output: JSON containing:

• success: boolean
• output_path: path to final video with Korean subtitles
• file_size_mb: size of output file

Note: FFmpeg must be installed on the system. The script checks for FFmpeg availability and provides installation instructions if needed.

Complete Example Workflow

# 0. Check environment setup (first time only)
python scripts/setup_check.py --auto-fix

# 1. Download video and subtitles
python scripts/download_youtube.py "https://www.youtube.com/watch?v=VIDEO_ID" downloads/

# 2. Extract subtitle texts
python scripts/extract_subtitle_text.py downloads/VideoTitle.en.srt > subtitle_texts.json

# 3. Gather context (manual step by Claude)
# - Analyze video metadata
# - Perform web searches
# - Create context file

# 4. Translate with Claude (manual step)
# - Read context file
# - Translate each subtitle text
# - Save to translated_texts.json

# 5. Merge translations with timestamps
python scripts/merge_translated_subtitle.py \
  downloads/VideoTitle.en.srt \
  translated_texts.json \
  downloads/VideoTitle.ko.srt

# 6. Burn subtitles into video
python scripts/process_video.py \
  downloads/VideoTitle.mp4 \
  downloads/VideoTitle.ko.srt \
  output/VideoTitle_korean.mp4

Key Advantages Over Automated Translation

This skill provides superior translation quality because:

1. Context-Aware: Claude understands the video's subject matter through metadata and web research
2. Terminology Consistency: Establishes and maintains consistent translation of key terms
3. Cultural Adaptation: Adapts content appropriately for Korean audiences
4. Tone Matching: Maintains the original video's tone and style
5. Quality Control: Claude can review and refine translations before finalizing

Prerequisites

The following must be installed on the system:

• Python 3.7+
• FFmpeg (for video processing)
• Python packages: yt-dlp, pysrt

Install Python dependencies:

pip install yt-dlp pysrt

Install FFmpeg:

# macOS
brew install ffmpeg

# Ubuntu/Debian
sudo apt-get install ffmpeg

Limitations

• Only processes videos with existing English subtitles (auto-generated or manual)
• Videos without subtitles are not currently supported
• Processing time depends on video length and translation thoroughness
• Large videos may take significant time for FFmpeg encoding

Scripts Reference

scripts/download_youtube.py

Downloads YouTube video and English subtitles, returns metadata including title and description.

scripts/extract_subtitle_text.py

Preprocesses SRT file and extracts text array for translation. Automatically handles YouTube's overlapping timestamp format.

scripts/merge_translated_subtitle.py

Combines translated text array with original SRT timing information to create Korean SRT file.

scripts/process_video.py

Uses FFmpeg to burn Korean subtitles into the video with customizable font styling.