feat(youtube): extract transcript highlights like Reddit comment gems

Add extract_transcript_highlights() that scores sentences by specificity
(numbers, proper nouns, topic relevance) and filters YouTube filler
(subscribe, welcome back, etc). Top 5 highlights shown as structured
bullets in compact output. Full transcript moved to collapsible <details>
block so the LLM reads highlights first, full text on demand.

SKILL.md updated to instruct the judge agent to quote highlights
directly in synthesis, same as Reddit top comments.

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

tests/test_youtube_yt.py

@@ -45,5 +45,36 @@ class TestYtDlpFlags(unittest.TestCase):
         self.assertIn("--no-cookies-from-browser", cmd)
 
 
+class TestExtractTranscriptHighlights(unittest.TestCase):
+    def test_extracts_specific_sentences(self):
+        transcript = (
+            "Hey guys welcome back to the channel. "
+            "In today's video we're looking at something special. "
+            "The Lego Bugatti Chiron took 13,438 hours to build with over 1 million pieces. "
+            "Don't forget to subscribe and hit the bell. "
+            "The tolerance on each brick is 0.002 millimeters which is insane for injection molding. "
+            "So yeah that's pretty cool. "
+            "Thanks for watching see you next time."
+        )
+        highlights = youtube_yt.extract_transcript_highlights(transcript, "Lego")
+        self.assertTrue(len(highlights) > 0)
+        # Should pick the sentences with numbers and topic relevance, not filler
+        joined = " ".join(highlights)
+        self.assertIn("13,438", joined)
+        self.assertNotIn("subscribe", joined)
+        self.assertNotIn("welcome back", joined)
+
+    def test_empty_transcript(self):
+        self.assertEqual(youtube_yt.extract_transcript_highlights("", "test"), [])
+
+    def test_respects_limit(self):
+        sentences = ". ".join(
+            f"The model {i} has {i * 100} parameters and runs at {i * 10} tokens per second"
+            for i in range(20)
+        ) + "."
+        highlights = youtube_yt.extract_transcript_highlights(sentences, "model", limit=3)
+        self.assertEqual(len(highlights), 3)
+
+
 if __name__ == "__main__":
     unittest.main()