feat: Add YouTube as 4th research source via yt-dlp

YouTube search and transcript extraction runs automatically when yt-dlp
is installed. Searches for topic videos from the last N days, fetches
auto-generated transcripts for top results, and feeds them through the
same scoring pipeline (relevance + recency + engagement) as Reddit/X.

New files:
- youtube_yt.py: search, transcript extraction, VTT cleanup

Modified files:
- schema.py: YouTubeItem dataclass, updated Report
- normalize.py: normalize_youtube_items()
- score.py: YouTube engagement scoring (views-dominated)
- dedupe.py: YouTube deduplication
- render.py: YouTube section in compact output
- env.py: is_ytdlp_available() check
- ui.py: YouTube progress messages
- last30days.py: _search_youtube(), parallel execution with Reddit/X
- SKILL.md: YouTube in stats box, citation priority
- README.md: YouTube docs, yt-dlp requirement, Peter shoutout

Inspired by Peter Steinberger's yt-dlp + summarize toolchain approach.

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

scripts/lib/env.py

@@ -196,6 +196,12 @@ def get_x_source(config: Dict[str, Any]) -> Optional[str]:
     return None
 
 
+def is_ytdlp_available() -> bool:
+    """Check if yt-dlp is installed for YouTube search."""
+    from . import youtube_yt
+    return youtube_yt.is_ytdlp_installed()
+
+
 def get_x_source_status(config: Dict[str, Any]) -> Dict[str, Any]:
     """Get detailed X source status for UI decisions.