/tt-hook-scripter

name: tt-hook-scripter
description: "Script the first 1-3 second TikTok hook: the spoken line, the on-screen text, and the opening visual firing at once so the viewer cannot swipe. Picks a 2026 hook formula (cold-open result, pattern interrupt, number reveal, open-loop question, relatable call-out, story) by goal of completion, saves, comments, or shares. The single biggest retention lever on TikTok. Use to script a hook from a video idea. Not for the caption (use tt-caption-writer) or scrubbing a script (use tt-humanizer)."

TikTok Hook Scripter

Write the first 1 to 3 seconds of a TikTok video: the spoken line, the on-screen text, and the opening visual, all firing at once. This is the single biggest lever on the whole platform. TikTok's ranker runs on completion rate, and a viewer decides to stay or swipe before second three. If the hook does not win, nothing downstream gets watched.

When to use

• User has a video idea and needs the opening to stop the scroll
• User's videos "die in the first second" and they want a stronger open
• User wants to pick a proven hook shape and fill it with their own angle
• Before filming, to lock the spoken line and the on-screen text

What this skill produces

For one video idea, a ready-to-film hook block:

• **Spoken line** (what you say to camera in the first 1-3 seconds)
• **On-screen text** (the muted-first promise, 3 to 7 words)
• **Opening visual** (what is in frame one: result, tension, or interrupt)
• **The formula used** and its primary goal
• **A loop-close note** (how to end the video so it restarts for a rewatch)

It does not write the caption (hand to `tt-caption-writer`) or the full body script beat-by-beat unless asked; it locks the open, which is where retention is won or lost.

Formulas this skill uses

| Code | Formula | Primary goal | Best for | |---|---|---|---| | T1 | Cold-Open Result | completion | show the finished outcome first, promise the how | | T2 | Pattern Interrupt | completion | break the expected frame so the thumb stops | | T3 | Specific-Number Reveal | saves | one odd, concrete number that reframes the topic | | T4 | Open Loop Question | comments | ask the exact question the video answers | | T5 | Relatable Call-Out | shares | a hyper-specific shared moment worth sending | | T6 | Bold Claim, No Hedge | comments | a flat contrarian claim the comments will argue | | T7 | Listicle Promise | saves | a numbered payoff with on-screen counters | | T8 | Story In Medias Res | completion | drop into the peak of a real story | | T9 | Tutorial Cold Start | saves | start step one with the result previewed | | T10 | Trend-Ride With A Twist | shares | a trending sound bent to your niche |

Full skeletons (three layers each) in `../../references/hook-formulas.md`.

Pick by goal first

| Goal | Reach for | |---|---| | Completion | T1, T2, T8 | | Saves | T3, T7, T9 | | Comments | T4, T6 | | Shares | T5, T10 |

Steps

**Voice profile first (all drafts).** If `../../references/voice-profile.md` has `filled: yes`, load it and match the user's voice fingerprint, hard rules, and CTA/link style throughout. If it is not filled, mention once that `tt-humanizer --mode profile` can learn their voice from a few posts, then proceed with the generic voice rules.

1. **Gather inputs.** The video idea, the niche/audience, the one promise the video delivers, and the goal (completion / saves / comments / shares). 2. **Pick the formula.** Use the goal table to shortlist, then suggest 2-3 that also fit the idea and let the user choose. For a trend ride (T10), hand the sound-fit question to `tt-trend-mapper` first. 3. **Write all three layers.** Spoken line, on-screen text, opening visual. The spoken line and the on-screen text MUST differ (muted-first viewing). Respect the 2026 rules:

• The result or the tension is in frame one. No greeting, no logo, no zoom.
• One specific number where the claim allows it.
• Say it the way a person talks; read it out loud.
• No AI vocabulary cluster (one marker is a slip; three in the hook is a

script). Em dashes: `..` for a breath in the spoken line, at most one on the on-screen card.

• No sincerity opener ("not gonna lie", "real talk") and no "Here's what

nobody tells you" reveal bridge; say the thing. 4. **Write the loop-close note.** How the last frame should land so a rewatch feels natural (a rewatch is almost a second view). 5. **Humanizer pass.** Run the spoken line through the `tt-humanizer` V3 rules to strip script tells before it ever reaches camera: AI vocab by density, stacked triads, reveal bridges, sincerity openers, written-not- spoken phrasing. Make it sayable; never insert a punch line for rhythm. 6. **Approval card.** Show: formula, the three layers, primary goal, the loop-close note, and an estimated hook duration. 7. **Hand off.** Offer `tt-caption-writer` for the caption and settings, and `tt-content-planner` if they are batching multiple hooks.

Hard rules

Global voice rules: see root `SKILL.md` Voice rules. Additional skill-specific rules:

• The hook is the first 1-3 seconds of the **video**, not the caption. Never let

the caption do the hook's job.

• The spoken line and the on-screen text are two different jobs. Do not repeat the

same words in both.

• Frame one shows something (result, tension, interrupt). No dead air, no intro.
• One specific number in the hook beats any adjective.
• The hook opens the loop; it never answers itself.

Anti-patterns (skill will refuse)

• "Hey guys" / "welcome back" / "in this video" openers.
• A logo animation or slow zoom before the words start.
• Reading the caption aloud as the hook.
• Promising a result the video never shows on screen.
• ALL CAPS spoken scripts (you cannot shout for 30 seconds).
• More than one em dash, or an AI vocabulary cluster, in the on-screen text.
• A staged punch line or "The result?" reveal inserted for rhythm.
• Five stacked calls