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linkedin-post

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LinkedIn writing coach — find topics from code history, draft posts following 2026 algorithm rules, review drafts. NOT auto-posting.

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1.2k downloads
Updated 2/15/2026

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SKILL.md

LinkedIn Post Skill

Writing coach for LinkedIn content. Based on Aviv Levi's 2026 algorithm guidelines (data-backed). Helps you:

  1. Find good topics from your actual work
  2. Draft posts optimized for the algorithm
  3. Review drafts against the 11 rules

This skill does NOT post anything. It drafts, you finish and publish.

Quick Commands

# Find topics from recent work
/linkedin-post topic

# Draft a post on a topic
/linkedin-post draft "How I built multi-agent consensus"

# Review a draft against the 11 rules
/linkedin-post review

# Learn to write better (structured practice modules)
/linkedin-post learn

# Generate weekly content schedule from git activity
/linkedin-post schedule

Reference

Full algorithm guidelines: linkedin-guidelines.md

Key Rules (Quick Reference)

#RuleWhy
1Dwell Time > LikesAlgorithm counts seconds, not clicks
2PDF/Carousels = 6.6%Highest engagement format
3Zero-ClickNo links in post body (use first comment)
4Mobile-first72% mobile, max 12 words/sentence
5Personal > Company1-2% organic on company pages
6Golden HourFirst 90 min = make or break
7Saves > Comments > LikesSave=100pts, Comment=10, Like=1
85 posts/weekConsistency flywheel (3-6 months)
9Authentic photos6.5x more engagement than stock
10Hook -> Meat -> CTAFixed structure every time
11CTA in commentsForces deeper engagement

Post Template

[HOOK - 3 lines, stop the scroll]

[MEAT - numbered value, short sentences]

[CTA - open question, invite discussion]

---
First comment: [link or "DM me for X"]

Install

Download ZIP
Requires askill CLI v1.0+

AI Quality Score

68/100Analyzed 2/20/2026

Solid LinkedIn writing coach skill with clear commands, reference table of 11 algorithm rules, and post template. Explicitly does not auto-post which is good for safety. However, heavily tied to specific repo context (git history integration, ralph component), deeply nested path indicates internal-only usage, and lacks tags for discoverability. Good technical accuracy and structure but limited reusability outside this specific project."

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Metadata

Licenseunknown
Version-
Updated2/15/2026
PublisherEtanHey

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