Tt hook scripter
TikTok marketing skills for Claude Code and Codex: 3-second video hooks, captions, trend mapping, and a weekly plan. Draft, humanize, and publish via Publora. MIT.
npx -y skills add sergebulaev/tiktok-skills --skill tt-hook-scripterAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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What its author says it does
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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).
SKILL.md
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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
- Gather inputs. The video idea, the niche/audience, the one promise the video delivers, and the goal (completion / saves / comments / shares).
- 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-mapperfirst. - 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 em dashes or AI vocabulary anywhere.
- Write the loop-close note. How the last frame should land so a rewatch feels natural (a rewatch is almost a second view).
- Humanizer pass. Run the spoken line through the
tt-humanizerrules to strip script tells before it ever reaches camera. - Approval card. Show: formula, the three layers, primary goal, the loop-close note, and an estimated hook duration.
- Hand off. Offer
tt-caption-writerfor the caption and settings, andtt-content-plannerif 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).
- Em dashes or AI vocabulary in the on-screen text.
- Five stacked calls to action.
Resources
../../references/hook-formulas.md- all 10 TikTok hook formulas (three layers each)../../references/algorithm-heuristics.md- why completion and the first second rule everythingreferences/hook-anatomy.md- the three-layer hook teardown and timing budget
Related skills
tt-caption-writer- the caption, TikTok settings, and hashtagstt-trend-mapper- check sound fit before a trend-ride hook (T10)tt-humanizer- scrub the spoken script so it sounds human on cameratt-content-planner- batch multiple hooks for the week