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kol-discovery

Identifies and ranks Key Opinion Leaders (KOLs) based on engagement metrics, active rate, and sentiment rather than just views.

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SKILL.md
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Skill: KOL Discovery Workflow

Objective: Find and rank Key Opinion Leaders (KOLs) based on strict performance metrics rather than just view counts.

Execution Steps:

  1. Search: Use search_youtube to find videos about the topic. If the user specifies a time frame (e.g., "last month"), use get_date_range first to get the published_after date string.
  2. Data Gathering: Use get_video_details and get_channel_details to fetch the underlying statistics for the top candidates.
  3. Evaluation:
    • For each candidate, calculate engagement_rate and active_rate using the calculate_engagement_metrics tool.
    • If needed, fetch comments and run analyze_sentiment_heuristic.
    • Calculate the match_score to rank them objectively.
  4. Reporting: Present the top KOLs in a clear table. Explain why they were chosen (e.g., "High Engagement of 12%, despite lower subscriber count"). Drop clickbait videos that have high views but terrible engagement metrics, and explicitly tell the user you filtered them out to save their time.

Next Actions: Once the list is presented, actively ask the user if they want to:

  • See a visual chart of the engagement metrics.
  • Generate and publish a final HTML report.
  • Do a deep-dive transcript reading on any specific video from the list.
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google/adk-samples
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