# Linkedin Engager Analytics

Pull the people who liked or commented on any LinkedIn post and segment them by ICP fit...

- Repository: https://github.com/sergebulaev/linkedin-skills (5474 stars)
- Category: Engineering
- License: MIT
- Last updated: 2026-10-27
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add sergebulaev/linkedin-skills --skill linkedin-engager-analytics -g -a claude-code -y`
Codex: `npx skills add sergebulaev/linkedin-skills --skill linkedin-engager-analytics -g -a codex -y`
Cursor: `npx skills add sergebulaev/linkedin-skills --skill linkedin-engager-analytics -g -a cursor -y`
Gemini CLI: `npx skills add sergebulaev/linkedin-skills --skill linkedin-engager-analytics -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add sergebulaev/linkedin-skills`

## Description

Pull the people who liked or commented on any LinkedIn post and segment them by ICP fit (peer / aspirational / prospect / other). Produces an engager roster, tier breakdown, and outbound action lists (follow back, comment-drop, DM-able with one-line openers). Powered by Apify, no LinkedIn login. Triggers on \"who liked my post\", \"who engaged\", \"engagers report\", \"audience analytics\". Not for tracking author replies to your comments (use linkedin-thread-monitor).

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# LinkedIn Engager Analytics

Pull every liker and commenter on a LinkedIn post and bucket them by ICP fit. Outputs a roster + action list you can feed into your DM or outreach queue.

Needs a read credential: `APIFY_TOKEN`, or the Apify MCP connector (the only option on claude.ai). With neither, falls back to user-paste of the engager list.

## When to use

- After publishing a post: "Who actually engaged? Are they ICP?"
- Before a campaign: "Pull the last 5 viral posts in my niche, group their commenters by company size"
- Reviewing competitor engagement: which prospects show up across multiple authors

## Input

- One or more LinkedIn post URLs
- Optional: ICP definition (target titles, company size, industry)
- Optional: max engagers per post (default 100)

## Output

Output format (engager roster, tier breakdown, action lists): see `references/output-spec.md`. Headline: a table of engagers labelled by ICP tier and a per-tier action list.

## Steps

1. **Fetch engagers.** Call `lib.ApifyClient.fetch_post_engagers(post_url=<url>, max_items=100)`. Returns a list of dicts with `type` ("commenters" | "likers"), `name`, `subtitle` (job title + company), `url_profile`, `content` (comment text if commenter), `datetime`. Cost is roughly $0.005 per engager-record. The underlying actor answers for one audience per run, so `max_items` is the total across both and is split evenly; pass `types=("likers",)` when only one side matters, or add `"reshares"` to include people who reposted.

The rest: https://github.com/sergebulaev/linkedin-skills/blob/HEAD/.codex-marketplace/linkedin-skills/skills/linkedin-engager-analytics/SKILL.md