LinkedIn Post Engagers
/linkedin-post-engagersReturns the people who reacted to a LinkedIn post: name, headline, profile URL and reaction type, one page of reactors per 0.3-credit call.
Overview
LinkedIn Post Engagers takes one LinkedIn post URL and returns the people who reacted to it, each with a name, headline, profile URL and reaction type, through the SyncGTM MCP `linkedin_post_engagers` tool. Results are paged: `page_number` runs 1 to 10, and each page is a separate call at 0.3 credits. It is the wider half of post-engagement sourcing, giving you several times more people than the commenters list on a softer signal.
What it does
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Takes one full LinkedIn post URL as `post_url`. One post per call. A profile URL, a company page URL or a bare post ID is not accepted.
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Returns the reactors: `name`, `headline`, `profile_url` and `reaction` (for example `LIKE`) for each person in the `engagers` array.
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Pages with `page_number`, 1 to 10. One call returns one page and is charged separately. Page 11 does not exist, so a post with thousands of reactions never fully unloads.
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Covers reactions only. The people who wrote a comment come from `linkedin_post_commenters` at the same 0.3 credits, and that is the warmer tier. Run both on the same post for full audience coverage.
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Returns no emails, no phone numbers, no company firmographics and no seniority field. Titles have to be read off the headline or confirmed with `linkedin_profile_enrich`, and emails come from `find_work_email` at 1 credit each.
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Costs 0.3 credits per call. All ten pages of one post is 3 credits; the real spend is the enrichment you run afterwards, so filter first.
How to use it
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Download the skill file — it saves as linkedin-post-engagers.zip.
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In Claude, open Settings → Capabilities → Skills and upload the .zip (or unzip the linkedin-post-engagers/ folder into .claude/skills/ for Claude Code).
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Connect the SyncGTM MCP server (browser sign-in, no API key), then run `check_credits` — it is free and confirms both the connection and your balance.
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Trigger /linkedin-post-engagers and paste the full LinkedIn post URL. Say how many pages you want, for example "pages 1 to 5", because one call returns one page.
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The one setting worth tuning is `page_number`. Start at page 1, read the headlines, and only page further when the audience is on ICP — then filter on headline before you spend anything on emails.
Use cases
Warm list from a competitor post
Take a competitor or category post about the problem you sell into and pull everyone who reacted to it. Those people raised their hand on your topic in public, without ever visiting your site.
Follow-up queue after your own post
Pull the reactors on the post your founder published last week and work them Monday morning. The reaction is the opener, so the first line writes itself.
Widen a thin commenter list
When a post only drew six comments, the reactor list usually runs several times longer. Use it to top up a warm segment that is too small to sequence.
Audience check before a sponsorship
Pull page 1 of reactors on a newsletter, event or creator post and read the headlines. It tells you whose audience actually shows up before you pay to reach it.
GTM workflow examples
Competitor post to a ranked outbound list
- 1Call `linkedin_page_posts` on the competitor's LinkedIn company page with `max_posts: 10` and pick the post about the problem you sell into, not a hiring or brand post.
- 2Call `linkedin_post_engagers` on that post URL for `page_number` 1 through 5 — 1.5 credits — and deduplicate the reactors by `profile_url`.
- 3Call `linkedin_post_commenters` on the same post URL, page 1, and merge on `profile_url`. Anyone in both lists is tier 1, commenters are tier 2, reactors are tier 3.
- 4Filter on `headline` down to VP Sales, Head of Sales and RevOps titles, then call `find_work_email` on the top 25 people only — 25 credits.
Outcome: A tier-ranked outbound list of up to 25 buyers who publicly engaged with a competitor's post, each with the exact post to quote in line one and a work email wherever `find_work_email` returned one.
Monday follow-up queue from Friday's founder post
- 1Call `linkedin_profile_posts` on the founder's profile with `max_posts: 5` to get last week's post `url` and its `engagement` counts.
- 2Call `linkedin_post_engagers` on that post for `page_number` 1 through 10 — 3 credits — stopping early on the first empty `engagers` array.
- 3Call `linkedin_post_commenters` on the same post, pages 1 and 2, and merge both lists so every person carries either a comment or a reaction type.
- 4Call `linkedin_profile_enrich` on the 20 people whose headline is too vague to judge — 20 credits — and read their current title and company off `experience`.
- 5Call `find_work_email` on the confirmed ICP subset only, at 1 credit each, and hand the rows to sequencing.
Outcome: A Monday morning queue of everyone who touched Friday's post, commenters first, with current titles confirmed and a work email on every ICP row that `find_work_email` resolved.
Launch post to an account map
- 1Call `linkedin_page_posts` on the partner or category leader's LinkedIn page to find the launch announcement post and its `posted_at` date.
- 2Call `linkedin_post_engagers` on that post URL for `page_number` 1 through 3 — 0.9 credits — and group the reactors whose `headline` names an employer by that company.
- 3For every company that appears two or more times, look up its website domain and call `find_people_within_company` with that `domain` plus a `job_title` array — 1.5 credits per call, flat, 5 profiles by default — to name the decision-makers who did not react.
- 4Call `find_work_email` on two contacts per account at 1 credit each and write the launch post itself into the first line of the sequence.
Outcome: An account map of the companies that showed up repeatedly in the reactor list, each with named decision-makers, work emails where `find_work_email` resolved one, and the dated launch post as the trigger.
Prompts
Paste any of these into Claude once the skill is installed and the SyncGTM MCP is connected.
Get the people who reacted to this LinkedIn post: https://www.linkedin.com/posts/example_activity-7261234567890123456-abcd — page 1 only. Return name, headline, profile URL and reaction type as a table.Run linkedin_post_engagers on https://www.linkedin.com/posts/example_activity-7261234567890123456-abcd for pages 1 to 5. Stop early if a page comes back empty, deduplicate by profile URL, and report the credits used.Pull linkedin_post_engagers pages 1 to 3 and linkedin_post_commenters page 1 on https://www.linkedin.com/posts/example_activity-7261234567890123456-abcd. Merge on profile URL, mark who did both, and rank commenters above reactors.From https://www.linkedin.com/posts/example_activity-7261234567890123456-abcd pull reactor pages 1 to 5, keep only VP Sales, Head of Sales and RevOps headlines, then run find_work_email on the top 20 only. Do not guess email patterns. Report total credits.Use linkedin_profile_posts with max_posts 5 on https://www.linkedin.com/in/example/, pick the post with the highest engagement, then run linkedin_post_engagers pages 1 to 3 on it and give me the deduplicated reactor list.Best practices
Say "reacted" or "liked", not "engaged". "Engaged" is ambiguous and your client may route the call to `linkedin_post_commenters` instead. For the inverse view — the posts one prospect reacted to — the right tool is `linkedin_profile_reactions` at 0.2 credits.
Ask for pages explicitly. One call returns one page at 0.3 credits, so "pages 1 to 10" means ten calls and 3 credits — and page 11 does not exist.
Test with page 1 before committing. Read the first page of headlines: if the audience is off ICP, the other nine pages will be too.
Filter on `headline` before enrichment. Filtering is free; sending 400 unfiltered reactors into `find_work_email` is 400 credits.
Rank commenters above reactors when you merge the two lists. A sentence is a stronger signal than a click, and both cost 0.3 credits.
Pick a problem post, not a brand or hiring post. And never write a sequence line claiming the person said something — they pressed a button.