kol-discovery

Find Key Opinion Leaders (KOLs) in a given domain by combining web research with LinkedIn post search. Given a company/idea and target domain, generates authority keywords, searches LinkedIn posts to find prolific authors with high engagement, and merges with web-researched influencers. Use when someone wants to "find influencers in X space" or "who are the KOLs for Y industry."

Quality

100%

Does it follow best practices?

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Adds up to 20 points to the overall score

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Securityby

Low

Low-risk findings worth noting

Quality

Content

100%

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 well-structured, actionable pipeline guide with executable commands, explicit validation steps, and a clean single-script bundle reference. It stays lean without teaching concepts Claude already knows.

Dimension	Reasoning	Score
Conciseness	The body is lean and assumes Claude's competence — phases, a concrete config JSON, command flags, and an output table, with no padding explaining basic concepts Claude already knows.	3 / 3
Actionability	Provides a fully executable command with documented flags, a concrete config JSON structure, and an explicit output CSV schema — copy-paste ready guidance.	3 / 3
Workflow Clarity	The pipeline is clearly sequenced across Phases 0–4 with explicit validation checkpoints ("Present keywords to user for approval before running", "Always run with --test first") and a refine feedback loop in Phase 3.	3 / 3
Progressive Disclosure	Well-organized into clear phases with a single one-level-deep bundle reference (scripts/kol_discovery.py, which exists) and no nested reference chains.	3 / 3
	Total	12 / 12 Passed

Description

100%

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 is specific, third-person, and provides explicit trigger guidance covering both what the skill does and when to use it. It is concise yet comprehensive with no vague fluff.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — "combining web research with LinkedIn post search", "generates authority keywords", "searches LinkedIn posts to find prolific authors with high engagement", and "merges with web-researched influencers" — matching the multiple-specific-actions anchor.	3 / 3
Completeness	Explicitly answers both what it does (the keyword/search/merge pipeline) and when to use it via a clear "Use when someone wants to..." clause, satisfying the both-what-and-when anchor.	3 / 3
Trigger Term Quality	Includes natural user phrasings like "find influencers in X space" and "who are the KOLs for Y industry" that a user would actually say, giving good trigger coverage.	3 / 3
Distinctiveness Conflict Risk	Occupies a clear niche (KOL/influencer discovery via LinkedIn post search) with distinct triggers unlikely to fire for unrelated skills.	3 / 3
	Total	12 / 12 Passed

Validation

93%

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 — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: gooseworks-ai/goose-skills
Path: skills/social/capabilities/kol-discovery/SKILL.md
Commit: 8866b2a

Reviewed: 1 day ago

Table of Contents

Discovery Implementation Validation

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