# 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…

- **Type:** Skill
- **Install:** `agentstack add skill-sergebulaev-linkedin-skills-linkedin-thread-monitor`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [sergebulaev](https://agentstack.voostack.com/s/sergebulaev)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [sergebulaev](https://github.com/sergebulaev)
- **Source:** https://github.com/sergebulaev/linkedin-skills/tree/main/skills/linkedin-thread-monitor
- **Website:** https://github.com/sergebulaev/linkedin-skills

## Install

```sh
agentstack add skill-sergebulaev-linkedin-skills-linkedin-thread-monitor
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# 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)
3. **Classify stage:**
   - Hot (72h): don't reply in thread. Consider DM
4. **Draft responses** for warm threads using `linkedin-reply-handler`.
5. **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)
6. **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](https://github.com/sergebulaev)
- **Source:** [sergebulaev/linkedin-skills](https://github.com/sergebulaev/linkedin-skills)
- **License:** MIT
- **Homepage:** https://github.com/sergebulaev/linkedin-skills

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

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-sergebulaev-linkedin-skills-linkedin-thread-monitor
- Seller: https://agentstack.voostack.com/s/sergebulaev
- Browse the marketplace: https://agentstack.voostack.com/browse

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