Linkedin Thread Monitor

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

1. Fetch user's recent comments. If APIFY_TOKEN is set, call lib.ApifyClient.fetch_user_recent_comments(username=, 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.
2. 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)

1. Classify stage:

• Hot (72h): don't reply in thread. Consider DM

1. Draft responses for warm threads using linkedin-reply-handler.
2. 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)

1. 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

Related skills

• 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

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: sergebulaev
• Source: sergebulaev/linkedin-skills
• License: MIT
• Homepage: https://github.com/sergebulaev/linkedin-skills

Install and usage instructions live in the source repository linked above.