kol-discovery

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

Quality

61%

Does it follow best practices?

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Securityby

Passed

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tessl review fix ./python/agents/youtube-analyst/youtube_analyst/skills/kol-discovery/SKILL.md

Quality

Content

72%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The content is a concise, well-structured orchestration guide that names concrete tools and a clear sequence, but it leaves the match_score computation unspecified and lacks validation checkpoints for a batch-ranking workflow.

Suggestions

Specify how match_score is computed (its inputs and weighting) or point to the tool/section that defines it, so the ranking step is fully actionable.

Add a validation checkpoint before reporting, e.g. verify each candidate has engagement and active-rate data and skip or flag entries with missing statistics.

Clarify how many 'top candidates' to gather in the Data Gathering step so the batch size is unambiguous.

Dimension	Reasoning	Score
Conciseness	The body is lean and assumes Claude's competence: it does not explain what a KOL or engagement rate is, and each step states only the action, tool, and purpose, so every token earns its place.	3 / 3
Actionability	It names specific tools in a clear sequence (search_youtube, get_video_details, calculate_engagement_metrics, etc.), but 'Calculate the match_score to rank them objectively' gives no formula or inputs, leaving a key detail unspecified.	2 / 3
Workflow Clarity	The four steps are clearly sequenced with conditionals (e.g. 'If the user specifies a time frame'), but this batch ranking workflow has no validation or verification checkpoints, which caps workflow clarity at 2.	2 / 3
Progressive Disclosure	This is a single-purpose skill under 50 lines with no need for external references, and its sections (Objective, Execution Steps, Next Actions) are well-organized, which the simple-skills note lets score 3.	3 / 3
	Total	10 / 12 Passed

Description

50%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description conveys the skill's purpose and distinguishing metrics clearly but omits any explicit 'when to use' trigger guidance. It is solid but generic enough to risk overlap with similar influencer-analysis skills.

Suggestions

Add an explicit trigger clause, e.g. 'Use when the user asks to find, rank, or vet Key Opinion Leaders or influencers rather than sorting by view count alone.'

Broaden trigger terms to include natural user phrasings such as 'influencers', 'creators', and 'YouTube channels' alongside 'KOLs'.

List a few more concrete outputs (e.g. 'produces a ranked table with engagement, active rate, and sentiment per KOL') to lift specificity toward the top anchor.

Dimension	Reasoning	Score
Specificity	The description names concrete actions ('Identifies and ranks') and specific metrics ('engagement metrics, active rate, and sentiment'), but only two high-level verbs rather than the multiple distinct operations the top anchor exemplifies.	2 / 3
Completeness	It clearly answers what the skill does, but there is no 'Use when...' clause or equivalent explicit trigger guidance, which per the judging guidelines caps completeness at 2.	2 / 3
Trigger Term Quality	'Key Opinion Leaders (KOLs)', 'engagement metrics', and 'sentiment' are relevant natural terms, but common user phrasings like 'influencers', 'creators', or 'YouTube' are missing, so coverage is partial.	2 / 3
Distinctiveness Conflict Risk	The KOL-discovery niche is somewhat specific, but without explicit triggers it could still overlap with broader influencer or social-media analysis skills.	2 / 3
	Total	8 / 12 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: google/adk-samples
Path: python/agents/youtube-analyst/youtube_analyst/skills/kol-discovery/SKILL.md
Commit: a862ebc

Reviewed: about 11 hours ago

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