Linkedin Hook Extractor
Skill Verified ActiveReverse-engineer the hook formula from a viral LinkedIn post URL. Returns which of the 10 canonical 2026 formulas it uses (anaphora, R.I.P., year-pivot, time-anchor, self-proving, odd-money, paid-vs-free, curiosity-gap, contrarian, comment-gate), why it worked, and a blank template. Use to learn from a competitor's post, not to write your own (use linkedin-post-writer).
To help users understand the underlying structure and psychological drivers of viral LinkedIn posts, enabling them to learn from successful content and inform their own content strategy.
Features
- Reverse-engineer hook formulas from LinkedIn posts
- Identify 10 canonical 2026 hook formulas
- Analyze post structure and psychological effectiveness
- Generate a blank template mapped to the post's topic
- Audit original posts for AI tells and outdated tactics
Use Cases
- Study competitor's viral posts to understand their success factors
- Learn proven content structures before drafting your own posts
- Identify effective hook patterns to apply to your content strategy
Non-Goals
- Writing new LinkedIn posts directly (use `linkedin-post-writer` instead)
- Analyzing posts that are not viral or publicly accessible
- Providing real-time LinkedIn engagement metrics
Execution
- info:Pinned dependenciesThe README mentions `pip install requests python-dotenv`, but specific versions are not pinned, nor is a lockfile explicitly mentioned for Python dependencies.
Installation
First, add the marketplace
/plugin marketplace add sergebulaev/linkedin-skills/plugin install linkedin-skills@linkedin-skillsQuality Score
VerifiedTrust Signals
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