mcpbeat

Linkedin Thread Monitor

sergebulaev/linkedin-linkedin-thread-monitor

Track which of your LinkedIn comments earned author replies. Flags the 6-24h warm-reply window where thread momentum peaks, classifies threads as hot/warm/cool/dormant, and routes warm ones to linkedin-reply-handler for follow-up drafts. Powered by Apify, no LinkedIn login. Triggers on "what threads need follow-up", "author replied", "monitor my comments". Not for analyzing likers on a post (use linkedin-engager-analytics).

This is a copy. The original lives at sergebulaev/linkedin-thread-monitor.

2k tokens
context cost
the whole folder, loaded on every use
3
files
instructions only
0
copies elsewhere
how many repositories repackaged it
473
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/sergebulaev/linkedin-skills --skill linkedin-thread-monitor

The instruction itself

11 sections, as written by the author

LinkedIn Thread Monitor

Track which of your comments earned author replies. The author-reply signal is the highest-value inbound LinkedIn produces; this skill ensures you respond inside the window where momentum compounds.

Depends on APIFY_TOKEN. Without it, falls back to user-paste of recent comment URLs.

When to use

  • Daily: "What threads need follow-up today?"
  • After posting a batch of comments: "Check back in 6 hours"
  • When an author replied personally: "Draft the response"

Input

  • Your LinkedIn handle (last path segment of profile URL, e.g. your-handle)
  • Optional: window in hours (default 72)

Output

Output format (daily report, warm-thread preview, weekly roll-up): see references/output-spec.md. Headline: a table of recent comments with author-reply status + recommended action.

Steps

  • Fetch user's recent comments. If APIFY_TOKEN is set, call lib.ApifyClient.fetch_user_recent_comments(username=<your-handle>, result_limit=30). Each item already includes the parent post body, post URL, post author, and reaction stats. If APIFY_TOKEN is not set, ask the user to list (or paste) the URLs of comments they've posted in the last 72h.
  • For each comment posted in last 72h: check the parent post's comment tree (use fetch_post_comments(post_id=..., scrape_replies=True)) for:
  • Replies to the user's comment
  • Whether the author posted any of those replies
  • Timestamps (time since user's comment, time since latest reply)
  • Classify stage:
  • Hot (<6h): author just replied. Respond within 90 min for max thread momentum
  • Warm (6-24h): the warm-reply window. Author replies most happen here
  • Cool (24-72h): still respondable but lower velocity
  • Dormant (>72h): don't reply in thread. Consider DM
  • Draft responses for warm threads using linkedin-reply-handler.
  • Flag suspicious patterns:
  • Author replied but also deleted someone else's comment (author is actively moderating, tread carefully)
  • Commenter is in thread self-promoting (your reply shouldn't engage them)
  • DM routing: if thread is dormant but the author engaged meaningfully, draft a DM that references the thread specifically.

Warm-reply window

Anchored to a 2026-04 data point: a CEO replied to Serge's comment 22h after the original post. Reply-rate distribution: 0-6h 70%, 6-24h 25% (higher quality), >24h rare. Follow-up timing: 0-6h reply respond within 90 min; 6-24h within 2h; >24h within 4h before it goes cold. See references/thread-timing.md for the full matrix.

Inbound-quality signals

High-quality = follow up: founder/operator title, company in ICP, active posting history, >10 mutual 2nd-degree connections, prior thoughtful comments on user's posts.

Low-quality = skip: generic praise, template language ("I'd love to hop on a quick call"), sales/agency profile with no operator history, same comment copy-pasted across many creators.

Hard rules

Global voice rules: see root SKILL.md §Voice rules. Additional skill-specific rules:

  • Never reply to a reply later than 72h after the thread's last turn. Switch to DM.
  • Never chain 3+ replies under one comment (thread spam).
  • If the author deleted their reply, do not reply. They reconsidered.
  • Don't DM a warm thread before first replying publicly (skips a step).

Cost accounting

| Action | Apify call | Cost (free tier) |

|---|---|---|

| Daily thread sweep (1 user, ~30 comments) | fetch_user_recent_comments once | $0.005 |

| Per-warm-thread context | fetch_post_comments(scrape_replies=True) | $0.005 each |

A typical creator running this skill 5 days/week stays well under the $5 free monthly credit.

Files

  • SKILL.md — this file
  • references/output-spec.md — daily report shape, warm-thread preview, weekly roll-up, sample run
  • references/thread-timing.md — the timing matrix with examples
  • linkedin-reply-handler — drafts the actual follow-up message for warm threads
  • linkedin-engager-analytics — analyze who liked/commented on a post (different surface)
  • linkedin-comment-drafter — drafts the initial comment that starts threads

How to use it

Copy the folder

Take sergebulaev/linkedin-linkedin-thread-monitor from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.