ClawHub

Linkedin Hook Extractor

Prompts

Analyze any viral LinkedIn post URL to identify its hook formula, structure, why it worked, and generate a blank template for your own writing.

Install

openclaw skills install linkedin-hook-extractor

LinkedIn Hook Extractor

Paste a viral LinkedIn post URL. Get back: which hook formula it uses, the exact structure, why it worked, and a blank template mapped to your topic.

When to use

  • User finds a viral post they want to study
  • User wants to replicate a specific creator's pattern (Jake Ward, Lara Acosta, etc.)
  • Before linkedin-post-writer to seed a draft with a proven structure

Input

A LinkedIn post URL (any type: activity, share, ugcPost).

Output

  • Formula identified (F1-F10 from linkedin-post-writer/references/hook-formulas.md) with confidence score
  • Structural breakdown:
    • Hook lines (first 210 chars)
    • Body architecture (sections + what each does)
    • Close pattern
    • Reaction-triggering devices (numbers, named entities, vulnerabilities)
  • Why it worked psychologically
  • Blank template filled with slot markers matched to the original, ready for the user's voice
  • Cautions: anything in the original post that would fail 2026 audit (em dashes, AI vocab, outdated tactics)

Steps

  1. Parse URL. lib.url_parser.parse_linkedin_url → post_urn.
  2. Fetch post body. HarvestAPI preferred; fall back to asking user to paste text.
  3. Classify. Match against the 10 formulas using features:
    • First 2 lines: anaphoric? question? confession? number-led?
    • Body: numbered list? dated receipts? ledger? teardown?
    • Close: mirror question? identity reframe? commitment?
  4. Score confidence. If multiple formulas fit, return top 2 with fit scores.
  5. Extract structure. Pull each logical section and label it by formula role.
  6. Generate blank template. Replace specifics with {slot} markers that match the user's topic.
  7. Audit the source. Flag any AI tells in the original so the user doesn't copy them.

Example

Input: https://www.linkedin.com/posts/dharmesh_every-b2b-software-company-is-or-should-activity-7448808898326654978-iW20

Output:

  • Formula: F10 Contrarian + Historical Receipts (confidence 0.72). Secondary: F5 Self-Proving Meta (0.28).
  • Hook (first 210 chars): "Every B2B software company is (or should be) building an agentic version of their product."
  • Body: single bold claim → 3 paragraphs of reasoning → specific list of product changes required
  • Close: implicit call to action ("Seen this play out in your market yet?")
  • Blank template: 
    Every {category} {bold claim}.

{Reasoning paragraph 1 — the forcing function}
{Reasoning paragraph 2 — what it requires}
{Reasoning paragraph 3 — what breaks if you don't}

{Closing question that invites reader to take a side}
  • Cautions: none (post is clean)

Formulas reference

See linkedin-post-writer/references/hook-formulas.md for the 10 canonical formulas with full skeletons.

Files

  • SKILL.md — this file
  • references/classification-rules.md — feature extraction + scoring heuristics

Related skills

  • linkedin-post-writer — use the extracted template to draft your own
  • linkedin-post-audit — audit your draft before shipping
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