linkedin-post-writer

The saved excerpt is a snapshot from review. The external source remains the complete and most current version.

---
name: linkedin-post-writer
description: "Draft LinkedIn posts from 16 tested hook formulas mapped to engagement goals (comments, reposts, likes, saves), with 2026 algorithm formatting rules and an AI-tell scrub pass before publishing."
category: marketing
risk: none
source: community
source_repo: sergebulaev/linkedin-skills
source_type: community
date_added: "2026-07-06"
author: sergebulaev
tags: [linkedin, copywriting, hooks, social-media, personal-brand, content-marketing]
tools: [claude, codex, cursor, gemini]
license: "MIT"
license_source: "https://github.com/sergebulaev/linkedin-skills/blob/main/LICENSE"
---

# LinkedIn Post Writer

## Overview

Drafts long-form LinkedIn posts using 16 hook formulas that were reverse-engineered from posts that outperformed their authors' baselines in 2025-2026, each with a reference engagement number. Instead of asking "what should I write", the workflow asks "what should this post earn" (comments, reposts, likes, or saves), shortlists 2-3 matching formulas, fills the chosen skeleton with the user's voice, then scrubs the draft for AI tells before it ships.

This is the flagship skill from [sergebulaev/linkedin-skills](https://github.com/sergebulaev/linkedin-skills), a 10-skill LinkedIn bundle (writer, humanizer, pre-publish audit, comment drafter, reply handler, hook extractor, content planner, profile optimizer, engager analytics, thread monitor) installable as a Claude Code or Codex plugin. This standalone version covers the drafting workflow; scheduling and publishing automation live in the full bundle.

## When to Use This Skill

- Use when the user says "write me a LinkedIn post about X"
- Use when the user has a topic and a rough angle but needs a hook and structure
- Use when the user wants to pick from proven post formats instead of improvising
- Use when a draft exists but the hook is weak and needs a formula-based rebuild
- Not for replying to comments or optimizing profiles; this skill only drafts posts

## How It Works

### Step 1: Gather inputs

Collect: topic, angle, target audience (founders, operators, marketers), desired length (short 300-500, medium 900-1,300, or long 1,500-1,900 characters), and any raw material the user already has (numbers, anecdotes, names).

### Step 2: Pick the formula by engagement goal first

Ask (or infer) what the post should earn, then shortlist:

| Goal | Earned by | Formulas |
|---|---|---|
| Comments | questions, contrarian takes, vulnerability | F4 Time-Anchor Confession, F10 Contrarian + Receipts, F12 Permission Slip, F9 Curiosity-Gap |
| Reposts | quotable maxims, tributes, "X isn't Y" distinctions | F14 Named Gratitude, F2 R.I.P. Obituary, F8 Paid-vs-Free Reversal |
| Likes | emotional stories, celebrations, status-strip | F11 Emotional Cold-Open, F13 Bait-and-Switch Reversal, F16 Status-Strip Humility |
| Saves | simplifications, exact how-to, frameworks | F15 Explain-to-Kids, F7 Odd-Precision Money Ledger, F8 Paid-vs-Free Reversal |

The full set of 16, with reference engagement:

| Code | Formula | Reference | Best for |
|---|---|---|---|
| F1 | Platform Risk Anaphora | 4,240 eng | Category and platform-risk arguments |
| F2 | R.I.P. Obituary | 3,822 eng | Era-ending claims, industry pivots |
| F3 | Year-over-Year Pivot | 494 eng, 3.74x baseline | Identity shifts, founder reflection |
| F4 | Time-Anchor Confession | 1,519+ eng | Vulnerability, voice reset |
| F5 | Self-Proving Meta | 1,082 eng, 435 comments | Commitments and tests in public |
| F6 | Comment-Gate Lead Magnet | 717-3,008 eng | List building (max once a month) |
| F7 | Odd-Precision Money Ledger | 1,755 eng, 9.4x baseline | Build logs, cost breakdowns |
| F8 | Paid-vs-Free Reversal | 550 eng, 19.64x baseline | Framework giveaways |
| F9 | Curiosity-Gap Teaser | 306 eng, 4.25x baseline | Surprise and behind-the-scenes stories |
| F10 | Contrarian + Historical Receipts | 3,083 eng | Sacred-cow takes backed by history |
| F11 | Emotional Cold-Open | high raw reach | R