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

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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>
This commit is contained in:
Matt Van Horn
2026-03-23 17:49:38 -07:00
parent 499074b564
commit 4d6224f79a
6 changed files with 99 additions and 6 deletions
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SKILL.md
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@@ -240,7 +240,7 @@ The script will automatically:
**Read the ENTIRE output.** It contains EIGHT data sections in this order: Reddit items, X items, YouTube items, TikTok items, Instagram Reels items, Hacker News items, Polymarket items, and WebSearch items. If you miss sections, you will produce incomplete stats.
**YouTube items in the output look like:** `**{video_id}** (score:N) {channel_name} [N views, N likes]` followed by a title, URL, and optional transcript snippet. Count them and include them in your synthesis and stats block.
**YouTube items in the output look like:** `**{video_id}** (score:N) {channel_name} [N views, N likes]` followed by a title, URL, **transcript highlights** (pre-extracted quotable excerpts from the video), and an optional full transcript in a collapsible section. **Quote the highlights directly in your synthesis** - they are the YouTube equivalent of Reddit top comments. Attribute quotes to the channel name. Count them and include them in your synthesis and stats block.
**TikTok items in the output look like:** `**{TK_id}** (score:N) @{creator} [N views, N likes]` followed by a caption, URL, hashtags, and optional caption snippet. Count them and include them in your synthesis and stats block.
@@ -303,9 +303,10 @@ The Judge Agent must:
3. Weight TikTok sources HIGH (they have views, likes, and caption content — viral signal)
4. Weight WebSearch sources LOWER (no engagement data)
5. **For Reddit: Pay special attention to top comments** — they often contain the wittiest, most insightful, or funniest take. When a top comment has high upvotes (shown as `💬 Top comment (N upvotes)`), quote it directly in your synthesis. Reddit's value is in the comments.
6. Identify patterns that appear across ALL sources (strongest signals)
7. Note any contradictions between sources
8. Extract the top 3-5 actionable insights
6. **For YouTube: Quote transcript highlights directly in your synthesis.** These are pre-extracted key moments from the video - treat them like Reddit top comments. Attribute to the channel name and include the actual quote. YouTube's value is in what creators SAY, not just their view counts.
7. Identify patterns that appear across ALL sources (strongest signals)
8. Note any contradictions between sources
9. Extract the top 3-5 actionable insights
7. **Cross-platform signals are the strongest evidence.** When items have `[also on: Reddit, HN]` or similar tags, it means the same story appears across multiple platforms. Lead with these cross-platform findings - they're the most important signals in the research.