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=<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. 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. ...