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linkedin-engagement-trackerlisted

Audit the user's LinkedIn commenting activity from the Taplio comment queue and history : what is still in draft, what is pending, what posted, what failed and why, how many comments and replies went out per day, and whether the commenting days line up with profile views and follower growth. Returns a status board, the fix for each failure, and 3 adjustments for next week. Use when the user asks did my comments go out, why did a comment fail, is engagement working for me, or wants a weekly engagement review. Requires the Taplio MCP to read the comment drafts and the analytics overview.
TaplioOfficial/taplio-linkedin-claude-skills · ★ 5 · AI & Automation · score 77
Install: claude install-skill TaplioOfficial/taplio-linkedin-claude-skills
# LinkedIn Engagement Tracker Commenting is a habit, and habits need a scoreboard. This skill reads the user's comment queue and history, explains every failure, and checks whether the effort shows up in profile views and followers. ## When to trigger The user says "did my comments go out", "why did that comment fail", "is my engagement working", "engagement review", "what is in my comment queue", "weekly engagement report". ## Inputs to ask for (only if missing) 1. The window : default the last 7 days. Up to 90 days for the correlation. 2. Whether to act on stale drafts (commit them, rewrite them, or leave them). ## Process 1. Orient. 2. Pull the queue and the history by status : draft, pending, posted, failed, cancelled. Paginate when the window is long. 3. Status board : counts per status in the window, comments versus replies, distinct posts and authors targeted, share on the user's own posts versus others. 4. Failures : for each failed or cancelled item, the reason and what to do (see the failure guide). For each pending item older than 24 hours, the likely cause and the check to make. For each draft never committed, its age and a recommendation. 5. Activity : comments posted per day, best day, gaps, average length. 6. Signal : pull the daily analytics for the same window and compare profile views and follower deltas on days with 3 or more posted comments versus the other days. Small samples, correlation only, say so. 7. Return 3 adjustments for next week. ## Fai