x-hook-extractor

name

x-hook-extractor

description

Reverse-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).

X Hook Extractor

Paste a viral tweet or thread URL. Get back: which hook formula it uses, the exact structure, why it worked, and a blank template you can fill with your own voice.

When to use

• User finds a viral tweet or thread they want to study
• User wants to replicate a specific creator's pattern
• Before x-post-writer or x-thread-builder, to seed a draft with a proven shape

Input

An X tweet or thread URL (x.com or twitter.com, /status/<id>). For a thread, the URL of the first tweet is best.

Output

• Formula identified (X1-X10 from ../../references/hook-formulas.md) with a confidence score
• Container: single tweet vs thread, and why that container fit the idea
• Structural breakdown:
  • The hook line (and for a thread, how tweet 1 opens the loop)
  • Body architecture (per-tweet roles for a thread)
  • The close (what earns the repost or bookmark)
  • Reaction-triggering devices (numbers, named entities, the open loop)
• Primary goal the original chased (replies / reposts / likes / bookmarks)
• Why it worked psychologically and algorithmically
• Blank template with {slot} markers matched to the original, ready for the user's topic
• Cautions: anything in the original that would fail a 2026 audit (em dashes, AI vocab, 3+ hashtags, link in tweet 1)

Steps

1. Parse the URL. lib.url_parser.parse_x_url(url) returns handle, tweet_id, url_type.
2. Get the text. This bundle has no built-in tweet reader, so ask the user to paste the tweet or the full thread text. (If they later wire an Apify tweet actor, read it automatically.)
3. Detect the container. One self-contained tweet, or a multi-tweet thread.
4. Classify against the 10 formulas using features:
   • Single tweet: a flat contrarian claim (X1)? one hard number (X2)? a personal metric/confession (X3)? a quote tweet adding a layer (X4)? a one-line-per- item list (X5)? a relatable shared moment (X6)?
   • Thread: a numbered teaching promise (X7)? a story starting at the tension (X8)? a surprising result with the mechanism withheld (X9)? a first-person "how I" teardown (X10)?
5. Score confidence. If two formulas fit, return the top 2 with fit scores.
6. Extract structure. Label each part by its role. For a thread, map tweet 1 (the loop), the front-loaded payoff, the body beats, and the closer.
7. Name the primary goal the original optimized for.
8. Generate a blank template with {slot} markers matched to the original shape and the user's topic.
9. Audit the source. Flag any AI tells in the original so the user does not copy them.

Example

See references/examples.md for worked teardowns.

Formulas reference

See ../../references/hook-formulas.md for the 10 canonical X formulas with full skeletons and goal tags.

Files

• SKILL.md - this file
• references/classification-rules.md - feature extraction + scoring heuristics
• references/examples.md - worked teardowns (single tweet and thread)

Related skills

• x-post-writer - use the extracted single-tweet template to draft your own
• x-thread-builder - use the extracted thread template
• x-humanizer --mode audit - audit your draft before shipping