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>
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+# Synthesis Instructions (HN version - with Hacker News)
+
+## Judge Agent: Synthesize All Sources
+
+After all searches complete, internally synthesize (don't display stats yet):
+
+1. Weight Reddit/X sources HIGHER (they have engagement signals: upvotes, likes)
+2. Weight YouTube sources HIGH (they have views, likes, and transcript content)
+3. Weight WebSearch sources LOWER (no engagement data)
+4. Identify patterns that appear across ALL sources (strongest signals)
+5. Note any contradictions between sources
+6. Extract the top 3-5 actionable insights
+
+## Internalize the Research
+
+CRITICAL: Ground your synthesis in the ACTUAL research content, not your pre-existing knowledge.
+
+Read the research output carefully. Pay attention to:
+- Exact product/tool names mentioned
+- Specific quotes and insights from the sources - use THESE, not generic knowledge
+- What the sources actually say, not what you assume the topic is about
+
+## Citation Rules
+
+CITATION RULE: Cite sources sparingly to prove research is real.
+- In the "What I learned" intro: cite 1-2 top sources total, not every sentence
+- In KEY PATTERNS: cite 1 source per pattern, short format: "per @handle" or "per r/sub"
+- Do NOT include engagement metrics in citations - save those for stats box
+- Do NOT chain multiple citations: "per @x, @y, @z" is too much. Pick the strongest one.
+
+CITATION PRIORITY (most to least preferred):
+1. @handles from X - "per @handle"
+2. r/subreddits from Reddit - "per r/subreddit"
+3. YouTube channels - "per [channel name] on YouTube" (transcript-backed insights)
+4. HN discussions - "per HN" or "per hn/username" (developer community signal)
+5. Web sources - ONLY when Reddit/X/YouTube/HN don't cover that specific fact
+
+URL FORMATTING: NEVER paste raw URLs. Use the publication name, not the URL.
+
+Lead with people, not publications. Start each topic with what Reddit/X users are saying/feeling, then add web context only if needed.
+
+## Output Format
+
+Display in this EXACT sequence:
+
+**FIRST - What I learned:**
+
+Write the synthesis narrative. Use bold topic headers. Keep it grounded in research.
+
+For RECOMMENDATIONS queries: Extract SPECIFIC NAMES, not generic patterns. List by popularity/mention count with "Sources:" line per item.
+
+For other queries: Write thematic paragraphs with KEY PATTERNS section.
+
+**THEN - Stats block:**
+
+Copy this EXACTLY, replacing only the {placeholders}:
+
+```
+---All agents reported back!
+├─ 🟠 Reddit: {N} threads │ {N} upvotes │ {N} comments
+├─ 🔵 X: {N} posts │ {N} likes │ {N} reposts
+├─ 🔴 YouTube: {N} videos │ {N} views │ {N} with transcripts
+├─ 🟡 HN: {N} stories │ {N} points │ {N} comments
+├─ 🌐 Web: {N} pages (supplementary)
+└─ 🗣️ Top voices: @{handle1} ({N} likes), @{handle2} │ r/{sub1}, r/{sub2}
+```
+
+If HN returned 0 stories, write: "├─ 🟡 HN: 0 stories (no results this cycle)"
+
+Calculate actual totals from the research output. Count posts/threads from each section. Sum engagement metrics.
+
+**LAST - Invitation:**
+
+```
+---I'm now an expert on {TOPIC}. Some things I can help with:
+- [Specific suggestion based on research finding 1]
+- [Specific suggestion based on research finding 2]
+- [Specific suggestion based on research finding 3]
+```
+
+SELF-CHECK before displaying: Re-read your "What I learned" section. Does it match what the research ACTUALLY says?