Kol Discovery Agent Skill

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

375 tokens

context cost

the whole folder, loaded on every use

files

instructions only

copies elsewhere

how many repositories repackaged it

10025

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/google/adk-samples --skill kol-discovery

The instruction itself

1 sections, as written by the author

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.

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How to use it

Copy the folder

Take google/kol-discovery from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.