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/cli/main.py

@@ -48,6 +48,7 @@ COMMAND_MODULES = {
     "github": "skill_seekers.cli.github_scraper",
     "pdf": "skill_seekers.cli.pdf_scraper",
     "word": "skill_seekers.cli.word_scraper",
+    "video": "skill_seekers.cli.video_scraper",
     "unified": "skill_seekers.cli.unified_scraper",
     "enhance": "skill_seekers.cli.enhance_command",
     "enhance-status": "skill_seekers.cli.enhance_status",
@@ -142,7 +143,6 @@ def _reconstruct_argv(command: str, args: argparse.Namespace) -> list[str]:
         # Handle positional arguments (no -- prefix)
         if key in [
             "source",  # create command
-            "url",
             "directory",
             "file",
             "job_id",