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youtube-viral-topic

youtube-viral-topic

Find recent viral YouTube videos for account-growth topic selection. Use when the user asks for YouTube 爆款, YouTube hot videos, 起号选题 from YouTube, niche video references, recent high-view videos, or videos ranked by views, likes, comments, freshness, and topic relevance without low-follower filtering.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: youtube-viral-topic description: Find recent viral YouTube videos for account-growth topic selection. Use when the user asks for YouTube 爆款, YouTube hot videos, 起号选题 from YouTube, niche video references, recent high-view videos, or videos ranked by views, likes, comments, freshness, and topic relevance without low-follower filtering.

YouTube Viral Topic

Use this skill to find recent YouTube videos that are already performing strongly in a niche. Do not make low-subscriber status the default logic.

Quick Start

Run the bundled script from this skill directory:

python3 scripts/search_youtube_viral_topic.py --topic "AI agent,Claude Code" --days 30 --min-views 10000 --limit 50 --format markdown

Required environment for live API calls:

export YOUTUBE_API_KEY="..."

You can also pass --api-key explicitly for one-off runs. Never write API keys into skill files or output artifacts.

Workflow

  1. Convert the user's niche into concise query clusters.
  2. Call YouTube search.list with type=video, order=viewCount, and publishedAfter for the requested recent window.
  3. Deduplicate video ids across queries.
  4. Batch-enrich videos through videos.list for statistics and metadata.
  5. Batch-enrich channels through channels.list for public subscriber counts.
  6. Filter only by viral strength:
    • view_count >= --min-views
    • like_count + comment_count * 2 >= --min-engagement only when the user sets --min-engagement
  7. Rank by viral_score, then view_count, then like_view_rate.
  8. Return JSON for automation or Markdown for human topic review.

Output Contract

Each result must preserve the source URL, video metrics, and optional channel context:

{
  "platform": "youtube",
  "content_id": "",
  "url": "",
  "title": "",
  "author_id": "",
  "author_name": "",
  "subscriber_count": 0,
  "published_at": "",
  "view_count": 0,
  "like_count": 0,
  "comment_count": 0,
  "hot_score": 0,
  "viral_score": 0,
  "evidence": []
}

For cross-platform tables, follower_count is still populated with YouTube channel subscribers when available, but it is not a default filter.

Read references/scoring.md before changing thresholds or combining YouTube results with other platforms.

Guardrails

  • Do not call the default output "low-fan" or "low-subscriber" results.
  • Treat subscriberCount as public rounded/abbreviated subscriber data, useful only as context.
  • If hiddenSubscriberCount is true or subscriber count is missing, keep the video eligible as long as it passes the viral filters.
  • Prefer API collection over browser scraping. Browser sessions should only be used when the user explicitly asks.
  • Use videos as topic signals, structure references, and hook references. Do not copy scripts or captions wholesale.
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