li-audit

The only honest source of what works for an account is that account. Every rule in every LinkedIn guide, including the ones in this pack, is a prior. The user's own last 30 posts are the evidence.

Input

Ask for whichever the user has:

• The post analytics export (LinkedIn: Analytics -> Content -> Export). CSV.
• Or a screenshot per post with impressions, reactions, comments, reposts.
• Or just the posts and their reaction counts, which is enough for a first pass.

Also read ~/.claude/linkedin/log.md if it exists, since it records which hook formula each post used.

What to actually measure

Raw impressions are the least useful number on the page, because they are mostly a function of how many people already follow the user. Compute these instead, and show the working:

metric	how	what it tells you
Engagement rate	(reactions + comments + reposts) / impressions	whether the post earned its reach
Comment ratio	comments / reactions	whether it started something or just got a nod
Reach multiple	impressions / follower count	whether it travelled past the existing audience
Save/send rate	if available	the strongest single predictor of future reach

Rank by engagement rate and reach multiple, not impressions. A post with 900 impressions and 40 comments beat the one with 12,000 impressions and 6.

Then find the pattern

With the top 5 and bottom 5 side by side, look for what actually separates them, and be willing to conclude something the user will not like:

• Hook formula. Which numbers from hooks.json are in the top 5?
• Format. Text, document, image, video.
• Length.
• Theme.
• Day and time - check this last, and only if the other four show nothing. It is almost never the cause, and it is where people want it to be.
• First-hour comments. Posts the user replied to inside an hour versus not.