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linkedin-profile-post-scraper

Scrape recent posts from LinkedIn profiles using Apify. Use when you need to monitor what specific people are posting on LinkedIn, track founder/exec activity, or gather LinkedIn content for competitive intelligence.

76

Quality

95%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

100%

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

An exemplary concise, actionable skill body: executable Quick Start, complete CLI reference, real bundled script, and tidy sections with no fluff. The single-task workflow is unambiguous and the script provides internal error/cost feedback, so no improvement is needed.

DimensionReasoningScore

Conciseness

The body is lean and assumes competence — a Quick Start with three copy-paste commands, a compact CLI flag table, a one-line cost note, and a short Notes list — with no padding or explanations of concepts Claude already knows, matching the 'lean and efficient; every token earns its place' anchor.

3 / 3

Actionability

It provides fully executable commands (real script path, real flags, real example URLs), a complete CLI reference table with defaults, and a referenced script (scripts/scrape_linkedin_posts.py) that exists and is runnable, matching the 'fully executable code/commands; copy-paste ready' anchor.

3 / 3

Workflow Clarity

This is a simple single-action skill (invoke one script); per the simple-skills carve-out, workflow clarity scores 3 when the single action is unambiguous, and the script itself handles polling, FAILED/ABORTED/TIMED-OUT states, timeouts, and prints a cost estimate before running, providing internal validation rather than leaving the operator without feedback.

3 / 3

Progressive Disclosure

The body is under 50 lines with no need for external references, organized into clear sections (Quick Start, CLI Reference, Cost, Notes); the only bundle file (scripts/scrape_linkedin_posts.py) is referenced by an accurate path and exists, satisfying the 'well-organized sections' criterion for simple skills.

3 / 3

Total

12

/

12

Passed

Description

90%

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 well-formed, third-person description with an explicit 'Use when...' trigger and good natural-language keywords. It is distinct and complete; the only weakness is that its secondary clauses reframe a single scraping action rather than enumerating multiple distinct concrete operations.

DimensionReasoningScore

Specificity

The description names a concrete primary action ("Scrape recent posts from LinkedIn profiles using Apify") and a domain, but the additional phrases ("monitor what specific people are posting," "track founder/exec activity," "gather LinkedIn content for competitive intelligence") restate one scraping capability as use cases rather than listing multiple distinct concrete operations, matching the 'names domain and some actions, but not comprehensive' anchor rather than the 'lists multiple specific concrete actions' anchor.

2 / 3

Completeness

It explicitly answers what ("Scrape recent posts from LinkedIn profiles using Apify") and when ("Use when you need to monitor what specific people are posting on LinkedIn, track founder/exec activity, or gather LinkedIn content for competitive intelligence"), matching the anchor that requires both an explicit what and an explicit 'Use when...' trigger clause.

3 / 3

Trigger Term Quality

It surfaces natural terms a user would say — "LinkedIn profiles," "posts," "what specific people are posting," "founder/exec activity," "competitive intelligence" — giving good coverage of likely phrasings rather than only technical jargon, matching the 'good coverage of natural terms users would say' anchor.

3 / 3

Distinctiveness Conflict Risk

The niche is narrow and specific (LinkedIn profile post scraping via a named Apify actor) with distinct triggers tied to monitoring individuals' LinkedIn activity, making it unlikely to fire for unrelated skills.

3 / 3

Total

11

/

12

Passed

Validation

100%

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

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
gooseworks-ai/goose-skills
Reviewed

Table of Contents

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