feat(quality): GOAT synthesis improvements - hybrid cross-source linking, YouTube synonyms, human-readable xref tags

Ran 15-way blinded comparison (5 topics x 3 versions). CROSS won all 5 topics
(4.74/5.0 avg vs HN 4.10, Base 3.73). Then improved CROSS further:

- dedupe.py: hybrid similarity (token+trigram Jaccard) at 0.40 threshold,
  cross-source links went from 3 to 13 items across 5 topics
- render.py: [xref: HN5, HN4] -> [also on: HN, Reddit] for human-readable tags
- youtube_yt.py: SYNONYMS dict so "hip hop" matches "rap" (0.33 -> 0.71 score)
- SKILL.md: instruction #7 tells Claude to lead with cross-platform signals

Validation: improved CROSS scores 4.38/5.0 vs original 3.98 (+0.40), wins 4/5
topics. Biggest gains in specificity (+0.8) and format compliance (+1.0).

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

scripts/lib/youtube_yt.py

@@ -45,10 +45,38 @@ STOPWORDS = frozenset({
 })
 
 
+# Synonym groups for relevance scoring (bidirectional expansion)
+SYNONYMS = {
+    'hip': {'rap', 'hiphop'},
+    'hop': {'rap', 'hiphop'},
+    'rap': {'hip', 'hop', 'hiphop'},
+    'hiphop': {'rap', 'hip', 'hop'},
+    'js': {'javascript'},
+    'javascript': {'js'},
+    'ts': {'typescript'},
+    'typescript': {'ts'},
+    'ai': {'artificial', 'intelligence'},
+    'ml': {'machine', 'learning'},
+    'react': {'reactjs'},
+    'reactjs': {'react'},
+    'svelte': {'sveltejs'},
+    'sveltejs': {'svelte'},
+    'vue': {'vuejs'},
+    'vuejs': {'vue'},
+}
+
+
 def _tokenize(text: str) -> Set[str]:
-    """Lowercase, strip punctuation, remove stopwords, drop single-char tokens."""
+    """Lowercase, strip punctuation, remove stopwords, drop single-char tokens.
+    Expands tokens with synonyms for better cross-domain matching."""
     words = re.sub(r'[^\w\s]', ' ', text.lower()).split()
-    return {w for w in words if w not in STOPWORDS and len(w) > 1}
+    tokens = {w for w in words if w not in STOPWORDS and len(w) > 1}
+    # Expand synonyms
+    expanded = set(tokens)
+    for t in tokens:
+        if t in SYNONYMS:
+            expanded.update(SYNONYMS[t])
+    return expanded
 
 
 def _compute_relevance(query: str, title: str) -> float: