linkedin-hook-extractor
Reverse-engineer the hook formula from a viral LinkedIn post URL. Returns which of the 16 canonical 2026 formulas it uses (anaphora, R.I.P., year-pivot, time-anchor, curiosity-gap, contrarian, comment-gate, emotional cold-open, named-gratitude, and 7 more), why it worked, and a blank template. Use to learn from a competitor's post, not to write your own (use linkedin-post-writer).
Profile →npx skills add sergebulaev/linkedin-skills --skill linkedin-hook-extractor --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 - Before `linkedin-post-writer` to seed a draft with a proven structure ## Input A LinkedIn post URL (any typ
What does the linkedin-hook-extractor skill do?
Reverse-engineer the hook formula from a viral LinkedIn post URL. Returns which of the 16 canonical 2026 formulas it uses (anaphora, R.I.P., year-pivot, time-anchor, curiosity-gap, contrarian, comment-gate, emotional cold-open, named-gratitude, and 7 more), why it worked, and a blank template. Use to learn from a competitor's post, not to write your own (use linkedin-post-writer).
How do I install it?
Run `npx skills add sergebulaev/linkedin-skills --skill linkedin-hook-extractor --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From sergebulaev/linkedin-skills, a repository with 357 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.