git:20260715.e7a9a48 to git:20260905.36277a3

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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).

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# 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

## 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 11 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 11 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