scrape-post-engagers

scrape-post-engagers is a Prospecting & lead research skill for AI agents, published by Othmane-Khadri in the YALC-the-GTM-operating-system repository on GitHub. Skillspace rates scrape-post-engagers B (81/100) and it passed the safety scan; the rating is based on static analysis only.

Pull the audience that engaged with a LinkedIn post — likers (reactors) and commenters — via Unipile, dedupe across endpoints, and persist them as a result set ready for qualification or campaign launch. Use when the user says 'scrape engagers from this post', 'who liked this LinkedIn post', 'who commented on this LinkedIn post', 'pull engagers from this URL', or 'get the audience of this post'. Side-effecting — calls Unipile and writes to the local SQLite DB.

Grade

B

Quality

81 / 100

Safety

Passed

GitHub stars

259

Unproven: rated by static analysis only, not yet compared head-to-head.

Not launch-quality. It is graded B with a clean safety verdict, but our quality filters exclude it: a model that read it found it written only for the repository it lives in. So it is not in our launch-quality set, the skills our MCP server searches and recommends. How launch-quality is decided

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

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