feat: add video tutorial scraping pipeline with per-panel OCR and AI enhancement

Add complete video tutorial extraction system that converts YouTube videos
and local video files into AI-consumable skills. The pipeline extracts
transcripts, performs visual OCR on code editor panels independently,
tracks code evolution across frames, and generates structured SKILL.md output.

Key features:
- Video metadata extraction (YouTube, local files, playlists)
- Multi-source transcript extraction (YouTube API, yt-dlp, Whisper fallback)
- Chapter-based and time-window segmentation
- Visual extraction: keyframe detection, frame classification, panel detection
- Per-panel sub-section OCR (each IDE panel OCR'd independently)
- Parallel OCR with ThreadPoolExecutor for multi-panel frames
- Narrow panel filtering (300px min width) to skip UI chrome
- Text block tracking with spatial panel position matching
- Code timeline with edit tracking across frames
- Audio-visual alignment (code + narrator pairs)
- Video-specific AI enhancement prompt for OCR denoising and code reconstruction
- video-tutorial.yaml workflow with 4 stages (OCR cleanup, language detection,
  tutorial synthesis, skill polish)
- CLI integration: skill-seekers video --url/--video-file/--playlist
- MCP tool: scrape_video for automation
- 161 tests passing

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

src/skill_seekers/mcp/server_fastmcp.py

@@ -98,6 +98,7 @@ try:
         scrape_docs_impl,
         scrape_github_impl,
         scrape_pdf_impl,
+        scrape_video_impl,
         # Splitting tools
         split_config_impl,
         submit_config_impl,
@@ -420,6 +421,55 @@ async def scrape_pdf(
     return str(result)
 
 
+@safe_tool_decorator(
+    description="Extract transcripts and metadata from videos (YouTube, Vimeo, local files) and build Claude skill."
+)
+async def scrape_video(
+    url: str | None = None,
+    video_file: str | None = None,
+    playlist: str | None = None,
+    name: str | None = None,
+    description: str | None = None,
+    languages: str | None = None,
+    from_json: str | None = None,
+) -> str:
+    """
+    Scrape video content and build Claude skill.
+
+    Args:
+        url: Video URL (YouTube, Vimeo)
+        video_file: Local video file path
+        playlist: Playlist URL
+        name: Skill name
+        description: Skill description
+        languages: Transcript language preferences (comma-separated)
+        from_json: Build from extracted JSON file
+
+    Returns:
+        Video scraping results with file paths.
+    """
+    args = {}
+    if url:
+        args["url"] = url
+    if video_file:
+        args["video_file"] = video_file
+    if playlist:
+        args["playlist"] = playlist
+    if name:
+        args["name"] = name
+    if description:
+        args["description"] = description
+    if languages:
+        args["languages"] = languages
+    if from_json:
+        args["from_json"] = from_json
+
+    result = await scrape_video_impl(args)
+    if isinstance(result, list) and result:
+        return result[0].text if hasattr(result[0], "text") else str(result[0])
+    return str(result)
+
+
 @safe_tool_decorator(
     description="Analyze local codebase and extract code knowledge. Walks directory tree, analyzes code files, extracts signatures, docstrings, and optionally generates API reference documentation and dependency graphs."
 )