linkedin-post-engagers skillA
linkedin-post-engagers is agent-read markdown (skill) from naveedharri/benai-skills: Scrape LinkedIn post engagers (commenters + reactors) from any profile or set of profiles, deduplicate them,.
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns 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
mdr add naveedharri/benai-skills/linkedin-post-engagers@git:20260723.0af5e11mdr add naveedharri/benai-skills/linkedin-post-engagers@sha256:adeda9f0c3aafed1Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_25olr64ncp4jcs6g)
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Versions
Audit of the latest version
- 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
naveedharri/benai-skills · 65 stars · license MIT · pushed 2026-09-16 · 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
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