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.

Quality

83%

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Securityby

Low

Low-risk findings worth noting

Quality

Content

81%Weight 40%Scale 1-5

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

A concise, highly actionable skill body with clean structure and a verified bundle script. Its main weakness is the absence of validation/error-handling guidance for a batch scraping operation, which caps workflow clarity.

Suggestions

Add an explicit validation checkpoint after the Apify run (e.g. checking the run succeeded and output is non-empty before processing), and a brief error-recovery note for failed or timed-out runs.

Clarify the batch workflow sequence for multiple profiles (scrape -> verify each run -> filter by date -> output) so the multi-profile path has a clear ordered flow.

Note what happens on common failure modes (invalid profile URL, token missing, rate limits) and how to respond.

Dimension	Reasoning	Score
Conciseness	Lean and efficient at ~45 lines; no padding or explanations of concepts Claude already knows, every section (Quick Start, CLI Reference, Cost, Notes) earns its place.	5 / 5
Actionability	Provides fully executable, copy-paste-ready commands with real profile URLs and flag combinations, plus a complete CLI reference table covering all options.	5 / 5
Workflow Clarity	Although simple and single-purpose, this is a batch operation scraping multiple profiles with no validation/verification checkpoint (e.g. checking the Apify run status, handling failures, or verifying output), which per the rubric caps workflow clarity at 3.	3 / 5
Progressive Disclosure	Well-organized short skill (under 50 lines) with clear section headers and a real referenced script (scripts/scrape_linkedin_posts.py) that exists in the bundle; structure is appropriate with no nested references.	5 / 5
	Total	18 / 20 Passed

Description

86%Weight 40%Scale 1-5

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, concise description that clearly states both what the skill does and when to use it, with concrete trigger phrases and a distinct niche. Minor room for improvement in action diversity and synonyms.

Dimension	Reasoning	Score
Specificity	Names the domain (LinkedIn profile posts via Apify) and several concrete actions (scrape posts, monitor activity, track founder/exec activity, gather competitive intelligence), though 'monitor/track/gather' are somewhat overlapping rather than distinct capabilities.	4 / 5
Completeness	Explicitly states what it does ('Scrape recent posts from LinkedIn profiles using Apify') and when to use it ('Use when you need to monitor... track... or gather LinkedIn content'), satisfying both what and when with concrete trigger phrases.	5 / 5
Trigger Term Quality	Includes natural phrases users would say ('monitor what specific people are posting', 'track founder/exec activity', 'LinkedIn content'), with only minor synonyms missing (e.g. no mention of 'feed' or 'history').	4 / 5
Distinctiveness Conflict Risk	The niche is clear and narrow (LinkedIn profile post scraping via a specific Apify actor) with distinct triggers unlikely to collide with general scraping skills.	5 / 5
	Total	18 / 20 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: gooseworks-ai/goose-skills
Path: skills/social/capabilities/linkedin-profile-post-scraper/SKILL.md
Commit: 2523432

Reviewed: 5 days ago

Table of Contents

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