LinkedIn Hook Writer

LinkedIn Hook Writer

> Invoke this skill whenever the user is writing, editing, or planning a LinkedIn post. > The goal: turn any raw insight into a post whose first 40-50 words earn distribution — because that's all LinkedIn's algorithm reads before deciding your fate.

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The One Fact That Governs Everything

LinkedIn's ranking model (internally called 360 Brew) reads only the first 40-50 words of a post — roughly the two lines visible above "see more" on mobile — before deciding whether to push it to feeds.

If those words fail:

• The reader doesn't click see-more → no dwell time signal
• The algorithm doesn't distribute → no reach
• Everything under the fold is dead weight

Every other rule in this skill is downstream of this one.

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Hard Rules

1. Pixel width, not character count. LinkedIn renders by pixels. "W" is ~4x wider than "i". Budget is ~110 width units per mobile line. Never trust a "150 characters" limit.
2. One post = one idea. Multiple ideas dilute attention. Pick the sharpest angle.
3. Never open with "I'm excited to announce", "Just wanted to share", or any throat-clearing verb. The algorithm deprioritizes these.
4. The hook opens a gap between what the reader expects and what you claim. Gap = curiosity = click. Format is just packaging.
5. The first 45 minutes decides reach. If perfection.

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Hook Templates (Copy-Paste Ready)

For AI/ML/Engineering (matches Bhavesh's positioning)

• "I fine-tuned [model] to [specific metric]. Here's what broke first."
• "Everyone's shipping AI agents. Nobody's shipping the eval harness."
• "[Common ML belief]. Wrong. Here's the actual failure mode:"
• "I studied [N] production LLM systems. [Surprising pattern]."

For Career / Job Search (per user memory: no placement-cell content)

• "I applied to [N] AI/ML roles in [timeframe]. Here's what actually got replies."
• "[Timeframe] ago I couldn't [skill]. Today [outcome]. What changed:"
• "The [industry] hiring bar just shifted. Most candidates haven't noticed."

For Build-in-Public

• "[Product name] launched [timeframe] ago. [Specific metric]. Here's what surprised me:"
• "I tried building [thing] with [tool]. It failed. Here's why that was the point:"

For Contrarian Takes

• "Everyone says [conventional wisdom]. I've built [N] systems and here's what actually happens:"
• "The most dangerous advice in [space] right now: [belief]."

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What Not To Post

Based on r/LinkedInLunatics and r/marketing sentiment:

• Humblebrag transformations — "I forgot my laptop, so I wrote code on paper, and here's what it taught me about leadership"
• Generic vulnerability posts — "here's what my [life event] taught me about [SaaS metric]"
• "Solution mode + reflection" template posts — instantly recognized as LinkedIn cringe
• Motivational quote + irrelevant photo
• "Excited to announce..." anything
• Reposts of your own reposts — kills your account's authority signal

The reader can smell formulaic content in 0.3 seconds. Better to post nothing than to post cringe.

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Skill Invocation Pattern

When the user says any of:

• "Write me a LinkedIn post about..."
• "Help me draft a LinkedIn hook for..."
• "This flopped, rewrite it..."
• "Turn this into a LinkedIn post..."
• "What should I post about [topic]?"

→ Load this skill. Ask clarifying questions from Step 1 if the insight isn't clear. Return 3 hook variants + a structured body draft + a validation checklist result.

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Sources

Synthesized from:

• Pierre Herubel (30M LinkedIn views/year, 100K+ view post breakdowns)
• Diandra Escobar (131-hook study across 21 currently-growing creators, 5 hook formats)
• Matt Gray (846K followers, 59M organic views/month, 24M-view single post)
• Reddit r/marketing + r/LinkedInLunatics (what to avoid)
• LinkedIn's public statements on AI-content demotion (~94% demoted)

Research date: July 2026.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: BhaveshKhaple
• Source: BhaveshKhaple/bhavesh-claude-skills
• License: MIT

Install and usage instructions live in the source repository linked above.