post-scorer

name

post-scorer

description

Score a LinkedIn post using real performance data. Pulls the user's own post history via Apify (or uses cached data) to identify what actually performs, then scores the draft against those patterns. Use this skill whenever the user says "score my post", "review my post", "rate this post", "give me feedback", "how good is this post", or pastes a LinkedIn post and asks for critique. Scores against real data, not generic advice. Designed for live scoring at events and everyday post review.

Post Scorer

CRITICAL: Auto-start on load

When this skill triggers, go straight to Step 1. Do not summarise. Do not explain the scoring method. Start immediately.

Step 1. Get the post

If the user already pasted a post in the same message, use it. Otherwise say:

Paste the LinkedIn post you want scored.

Wait for the post.

Step 2. Load scoring data

The scorer needs two things: the user's voice system and real performance data.

Voice system

Read about-me.md and voice.md from the project if they exist. If missing, note it and score without voice matching.

Performance data

Check for cached LinkedIn data in the project or outputs folder. Look for files matching *-all-posts.json or *-posts.txt.

If cached data exists, use it. If not, ask the user:

[
  {
    "question": "To score your post against real data, I need your LinkedIn history. How should I get it?",
    "header": "Data source",
    "multiSelect"