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kol-content-monitor

Track what key opinion leaders (KOLs) in your space are posting on LinkedIn and Twitter/X. Surfaces trending narratives, high-engagement topics, and early signals of emerging conversations before they peak. Chains linkedin-profile-post-scraper and twitter-mention-tracker. Use when a marketing team wants to ride trends rather than create them from scratch, or when a founder wants to know which topics are resonating with their audience.

68

Quality

82%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

65%

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

Highly actionable with concrete commands and a clear phase sequence, but it is a monolithic single-file skill with a verbose output template and lacks validation/retry checkpoints for its batch scraping steps.

Suggestions

Add validation checkpoints after Phase 1/2 scraping (e.g., check for empty results or API errors and retry/handle before clustering) to lift workflow clarity for this batch operation.

Move the long Phase 4 output template into a references/ file (e.g. OUTPUT_TEMPLATE.md) and reference it from SKILL.md to improve progressive disclosure and reduce inline tokens.

Trim the Phase 5 content-calendar block and the output template prose to the essential fields to improve conciseness.

DimensionReasoningScore

Conciseness

It does not pad with concepts Claude already knows, but the Phase 4 output template (~60 lines) and the content-calendar block are long inline material that could be trimmed; mostly efficient but could be tightened, matching score 2 rather than the lean score 3.

2 / 3

Actionability

Executable shell commands with real flags, a concrete config JSON schema, numeric filter thresholds, explicit clustering steps, a cron line, and a cost table — copy-paste ready, matching the fully-executable anchor.

3 / 3

Workflow Clarity

Phases 0–5 are clearly sequenced, but this is a batch scraping operation across many profiles/handles with no validation or retry checkpoints (empty results, rate limits, scrape failures), which per the rubric caps workflow clarity at 2 rather than 3.

2 / 3

Progressive Disclosure

With no bundle files present, everything (config schema, both scraper commands, clustering logic, the full output template, calendar, scheduling, costs) lives inline in one SKILL.md; the long output template especially is content that could be split out, so it sits at score 2 rather than a well-split score 3.

2 / 3

Total

9

/

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.

A strong description: specific actions, explicit natural-language triggers, a clear what-and-when structure, and a distinct niche. No meaningful changes needed.

DimensionReasoningScore

Specificity

Names multiple concrete actions ('Track what KOLs…are posting', 'Surfaces trending narratives, high-engagement topics, and early signals') tied to a specific domain, matching the multi-action anchor rather than the partial-action score 2.

3 / 3

Completeness

It states what it does (track/surface KOL posts) and gives an explicit 'Use when a marketing team wants to ride trends… or when a founder wants to know which topics are resonating' clause, answering both what and when.

3 / 3

Trigger Term Quality

Natural phrasings a user would say appear directly — 'trending narratives', 'high-engagement topics', 'topics are resonating', 'ride trends' — giving good coverage rather than just a single relevant keyword.

3 / 3

Distinctiveness Conflict Risk

The KOL-content-monitor niche is clearly scoped, names the specific upstream skills it chains, and uses distinct triggers unlikely to fire for unrelated skills.

3 / 3

Total

12

/

12

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
gooseworks-ai/goose-skills
Reviewed

Table of Contents

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