| name | kol-discovery |
| description | Identifies and ranks Key Opinion Leaders (KOLs) based on engagement metrics, active rate, and sentiment rather than just views. |
Skill: KOL Discovery Workflow
Objective: Find and rank Key Opinion Leaders (KOLs) based on strict performance metrics rather than just view counts.
Execution Steps:
- 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.
- Data Gathering: Use
get_video_details and get_channel_details to fetch the underlying statistics for the top candidates.
- 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.
- 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.
