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LinkedIn Hook Extractor · sergebulaev | DecimalAI

marketingby sergebulaev

LinkedIn Hook Extractor

sergebulaev/linkedin-hook-extractor

Source sergebulaev/linkedin-skills ↗License MIT

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).

SkillScore84Maintained

Automatic

Marketing & Content pack

Last verified 8/19/2026

What it changes

Passed 21 of 25 test cases with the skill, and 14 of 25 without it.

Without skill56%

With skill84%

Checks it passed that the model alone missed

classifies the formula as F16 Status-Strip
identifies the formula as F12 Permission Slip
classifies the formula as F15 Explain-to-Kids

and 6 more in the full report

8 fixed13 passed either way3 still failing1 broke

Pass-rate lift: +28 pp
Tokens: +43%
Agent turns: 0%
Response time: +5%

Model gemini-3.6-flashMeasured 8/19/2026v121 of 25 cases passed with skill

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/sergebulaev-linkedin-hook-extractor/SKILL.md https://app.decimal.ai/s/sergebulaev-linkedin-hook-extractor/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add sergebulaev-linkedin-hook-extractor, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/sergebulaev-linkedin-hook-extractor/ and pins it in .decimal/skills.lock

decimalai skills add sergebulaev-linkedin-hook-extractor

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/sergebulaev-linkedin-hook-extractor/SKILL.md https://app.decimal.ai/s/sergebulaev-linkedin-hook-extractor/SKILL.md

Raw file: /s/sergebulaev-linkedin-hook-extractor/SKILL.md ↗ · machine-readable summary at /s/sergebulaev-linkedin-hook-extractor.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 8 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 8

Prompt

I found a high-performing post on LinkedIn (https://www.linkedin.com/posts/example-user_activity-7123456789-abc1) and want to study how it's built. Can you analyze the link, identify its hook pattern with a confidence rating, break down its section structure and emotional triggers, explain why it works psychologically, provide a slot-filled blank template tailored for product management, and point out any AI writing tells or outdated tactics in the original text?

What was checked, without and with the skill
Checked	Without skill	With skill
asks the user to paste the post text when unable to fetch the URL	Passed	Passed
uses formula classification identifiers F1 through F16 for formula identification	Missed	Passed
includes a confidence score for the formula fit	Passed	Passed

case-01 · gemini-3.6-flash · 8/19/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md57 lines3 files

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-F16 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, AI vocab, outdated tactics)

Steps

Parse URL. lib.url_parser.parse_linkedin_url → post_urn.
Fetch post body. If APIFY_TOKEN is set, call lib.ApifyClient.fetch_post(url). Otherwise ask the user to paste the text.
Classify. Match against the 16 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).
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.

Track record

Benchmark

21 / 25

test cases passed, vs 14 / 25 without

Adoption

Users: 1
Times used: 15

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/3/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

sergebulaev / linkedin-skills

skills/linkedin-hook-extractor/SKILL.md

View on GitHub ↗

License MITImported 8/3/2026Version v1Bundled 2 files

Other skills for the same job

Published skills whose descriptions closely match this one, with their headline benchmark lift.

hashgraph-online/x-hook-extractorReverse-engineer the hook from a viral X (Twitter) tweet or thread URL. Identifies which of the 10 canonical 2026 X formulas it uses (one-liner contrarian, data-point, build-in-public, quote-tweet, mini-list, relatable cold-open, listicle-thread, story thread, curiosity-gap, how-I teardown), explains why it worked, and returns a blank template mapped to your topic with its primary goal. Use to learn from a tweet you admire. Not for writing your own (use x-post-writer or x-thread-builder).Close match+73 pp pass-rate lift

More skills from the same source and nearby in the registry, with their headline benchmark lift.

Ready to supercharge your AI agents?

See it in action

What's inside

LinkedIn Hook Extractor

When to use

Input

Output

Steps

Track record

Benchmark

Adoption

SkillSafety

Source

Other skills for the same job

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