linkedin-hook-extractor Checked

Reverse-engineer the hook formula from a viral LinkedIn post URL. Returns which of the 20 canonical 2026 formulas it uses (anaphora, R.I.P., year-pivot, time-anchor, curiosity-gap, contrarian, comment-gate, emotional cold-open, named-gratitude, and 11 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).

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.

Reverse-engineer the hook formula from a viral LinkedIn post URL. Returns which of the 20 canonical 2026 formulas it uses (anaphora, R.I.P., year-pivot, time-anchor, curiosity-gap, contrarian, comment-gate, emotional cold-open, named-gratitude, and 11 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).

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 type: activity, share, ugcPost).

Output

• **Formula identified** (F1-F20 from ../../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• **Cautions:** anything in the original post that would fail 2026 audit (em dashes above the cap, AI vocab, outdated tactics), plus the 2026 reach-note flags from ../../references/hook-formulas.md: a question as line 1, a "Here's what/how" or "Stop X, start Y" opener, a "The result?" / "Plot twist:" bridge, an unpaid curiosity gap, "comment X to get Y" bait, or announced candor with no dated fact. A viral source post may have used these; the template should not copy them.

Steps

1. **Parse URL.** lib.url_parser.parse_linkedin_url → post_urn.

2. **Fetch post body.** If APIFY_TOKEN is set, call lib.ApifyClient.fetch_post(url). Otherwise ask the user to paste the text.

3. **Classify.** Match against the 20 formulas using features:

• First 2 lines: anaphoric? question? confession? number-led?
• Body: numbered list? dated receipts? ledger? teardown?
• Close: mirror question? identity reframe? commitment?
• F11-F16 cues: in-medias-res emotional scene with no setup (F11 Emotional Cold-Open); "I don't know who needs to hear this" reassurance (F12 Permission Slip); fake-bad-news that resolves positive (F13 Bait-and-Switch); a roll-call of named people thanked (F14 Named Gratitude); "{jargon} explained to kids" glossary (F15 Explain-to-Kids); "outside I'm called X, at home none of it survives" (F16 Status-Strip).

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