linkedin-post-engagers SKILL.md skillA

linkedin-post-engagers from naveedharri/benai-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add naveedharri/benai-skills/linkedin-post-engagers@git:20260723.0af5e11

Pins git:20260723.0af5e11 in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
naveedharri/benai-skills
Path
plugins/benai-sales/skills/linkedin-post-engagers/SKILL.md
Versions recorded
1
Latest version
git:20260723.0af5e11, committed Jul 23, 2026
Size
6,131 bytes
Repository stars
78
License
MIT

Scrape LinkedIn post engagers (commenters + reactors) from any profile or set of profiles, deduplicate them,.

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# LinkedIn Post Engagers

You are orchestrating a pipeline that extracts warm prospects from LinkedIn post engagements. People who comment on or react to LinkedIn posts are warm leads because they've already shown interest in a relevant topic. This skill turns that engagement data into an enriched, optionally qualified, deduplicated lead list.

Cold outbound starts from zero context. Post-engager prospecting starts from a signal: these people already cared enough about a topic to engage publicly. That makes them warmer than any scraped list, and the engagement itself gives you something to reference in outreach.

## CRITICAL Rules (Apply to the Whole Pipeline)

Read `references/apify-operations.md` before running any Apify actor. It is the source of truth for actor mechanics. Non-negotiables:

- **Schema first**: Before running ANY actor, call `call-actor` with `step: "info"` to get the current input schema. Never hardcode field names without checking.
- **Timeout handling**: Actor calls timeout at ~30 seconds via MCP. This is normal; the run continues server-side. Follow the polling pattern in the reference for EVERY actor call.
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add naveedharri/benai-skills/linkedin-post-engagers@sha256:adeda9f0c3aafed1

The line at the top of this page pins the label git:20260723.0af5e11, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_25olr64ncp4jcs6g.svg)](https://markdownregistry.com/a/art_25olr64ncp4jcs6g)

4 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 1 version of this file, committed on Jul 23, 2026.

versioncommittedcommitsizeaudit
git:20260723.0af5e11 latest2026-07-23 0af5e11 6,131 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (6131 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

naveedharri/benai-skills · 78 stars · license MIT · pushed 2026-10-09 · branch develop

API

GET https://markdownregistry.com/api/v1/artifacts/art_25olr64ncp4jcs6g
GET https://markdownregistry.com/api/v1/resolve?ref=naveedharri/benai-skills/linkedin-post-engagers
GET https://markdownregistry.com/api/v1/blob/adeda9f0c3aafed18efbbe646fb90b1892eaf35a191ba72fdae3b10d7991a502

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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Every file in naveedharri/benai-skills

Other files named linkedin-post-engagers

linkedin-post-engagers SKILL.md skill
naveedharri/benai-skills · plugins/all-skills/skills/linkedin-post-engagers/SKILL.md · Scrape LinkedIn post engagers (commenters + reactors) from any profile or set of profiles, deduplicate them,
git:20260723.0af5e11 · audit A · 78 stars

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