Tt Hook Scripter Agent Skill

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.

Never invent the specifics. The rules below ask for a concrete number, a date and a named entity, because that is what separates a real post from a generated one. Take them from what the user actually said in this conversation. Do not invent a figure, a date, a client name or a result, and do not soften a vague claim into a plausible-looking number. If the user has nothing concrete for a beat, ask them once, and if they still have nothing, drop the claim rather than decorate it. A published invented number is a retraction; a missing one is only a weaker post.

• 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-mapper first.

• 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.

• 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-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.

• Approval card. Show: formula, the three layers, primary goal, the

loop-close note, and an estimated hook duration.

• 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 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 everything
• references/hook-anatomy.md - the three-layer hook teardown and timing budget

Related skills

• tt-caption-writer - the caption, TikTok settings, and hashtags
• tt-trend-mapper - check sound fit before a trend-ride hook (T10)
• tt-humanizer - scrub the spoken script so it sounds human on camera
• tt-content-planner - batch multiple hooks for the week