Linkedin Hook Extractor
/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-writerto 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- Cautions: anything in the original post that would fail 2026 audit (em dashes, AI vocab, outdated tactics)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
- Parse URL.
lib.url_parser.parse_linkedin_url→post_urn. - Fetch post body. HarvestAPI preferred; fall back to asking user to paste text.
- 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?
- Score confidence. If multiple formulas fit, return top 2 with fit scores.
- Extract structure. Pull each logical section and label it by formula role.
- Generate blank template. Replace specifics with
{slot}markers that match the user's topic. - 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 filereferences/classification-rules.md— feature extraction + scoring heuristics
Related skills
linkedin-post-writer— use the extracted template to draft your ownlinkedin-post-audit— audit your draft before shipping
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install linkedin-hook-extractor - After installation, invoke the skill by name or use
/linkedin-hook-extractor - Provide required inputs per the skill's parameter spec and get structured output
What is Linkedin Hook Extractor?
Analyze any viral LinkedIn post URL to identify its hook formula, structure, why it worked, and generate a blank template for your own writing. It is an AI Agent Skill for Claude Code / OpenClaw, with 85 downloads so far.
How do I install Linkedin Hook Extractor?
Run "/install linkedin-hook-extractor" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Linkedin Hook Extractor free?
Yes, Linkedin Hook Extractor is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Linkedin Hook Extractor support?
Linkedin Hook Extractor is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Linkedin Hook Extractor?
It is built and maintained by Sergey Bulaev (@sergebulaev); the current version is v1.0.0.