# Universal rules — apply to every video model

These rules apply to Seedance, Kling, Veo, and any other AI video generator. They exist because all current video models share a common failure mode. They reward concrete physical direction. They punish abstraction, contradictions, and keyword spam. Ignoring these produces muddy generations regardless of which model you target.

Read this file after `dramaturgy.md` and before any model-specific file. The model-specific syntax sits on top of these rules — it does not replace them.

## Contents

1. The non-negotiable. Details intensify emotion (Details Law)
2. U1. Universal prompt skeleton
3. U2. Weight-at-start
4. U3. Show don't tell
5. U4. Natural language beats tag spam
6. U5. One primary camera move per shot
7. U6. Precise lens language
8. U7. Character consistency anchor
9. U8. No contradictions
10. U9. Concrete physical detail over abstract concept
11. U10. Duration discipline
12. U11. The final image rule
13. U12. The three-detail check (audit before sending)
14. U13. Reference role discipline
15. U14. Priority declaration

---

## 1. The non-negotiable. Details intensify emotion. Laziness kills the prompt.

This is the most violated rule in AI video, and the one reason most multi-shot prompts fail. The dramaturgy is fine — the writer just got lazy on a single shot, and that one thin shot drags the whole sequence into mush.

Every shot in every prompt owns at least three concrete physical details:

1. **One environmental pressure.** Cold blue refrigerator light. Steam off boiling water. Wet asphalt. Flickering fluorescent. Dripping tap. Curtain breathing in the AC. (Kurosawa: weather is a character. See `dramaturgy.md` §9.)
2. **One physical micro-action.** Jaw locks. Knuckles whiten on the fork. Lips press into a line. He swallows hard. Fingers curl against the doorframe. (Show, not tell — the body is the only place where feelings render.)
3. **One sound anchor or visual motif.** Stomach growl at 2.3s. Reflection in a darkened phone screen. Rain on the same windowpane. A single fluorescent flicker before each cut.

If a shot has none of these — it is filler. Delete it or rewrite it. No exceptions for "establishing", "transition", or "hero product" shots — those are exactly the shots that go lazy first.

Words that do not render and mark the writer being lazy:

- "cinematic", "professional", "high quality", "masterpiece", "stunning", "epic", "amazing"
- "beautiful lighting", "dynamic camera", "intense moment", "powerful scene"
- "he is sad", "she is angry", "he is afraid" — emotions named without a body

Replace each with concrete physical facts. The full theory of why this works lives in `dramaturgy.md` §2 (Second law).

## 2. U1. Universal prompt skeleton

Build every prompt from these layers, roughly in this order:

```text
[Subject / Character]
[Action / Motion]
[Scene / Environment]
[Camera / Shot / Lens]
[Lighting / Atmosphere]
[Style / Mood / Palette]
[Sound / Audio]
[Duration / Aspect ratio / Resolution]
[Continuity rules]
[Negative constraints — only if the model supports them]
```

Model-specific skeletons live in their reference files (`seedance.md`, `kling.md`, `veo.md`). For dramatic / multi-shot / character-locked Seedance work, the production-grade 11-block skeleton in `seedance.md` §6 supersedes this generic skeleton.

## 3. U2. Weight-at-start

Generators put more attention on the first 30-40% of tokens. Lead with subject and action. Style modifiers go at the end. Camera, lighting, and environment live in the middle.

## 4. U3. Show don't tell

The model cannot render feelings. It renders bodies. Translate every emotion into a physical action.

- Bad. "He is scared."
- Good. "His jaw locks. He stops breathing for one beat. His fingers curl against the doorframe."

Calibration: for one emotional transition, **2-4 observable cues** (eye movement, brow tension, mouth, breathing, throat swallow, hands) are enough. Fewer leaves the model guessing; more reads as overacting.

## 5. U4. Natural language beats tag spam

Video models are not image models. Tag stuffing like "masterpiece, 4k, cinematic, beautiful" fails. Write in full cinematic sentences as if briefing a human DOP.

## 6. U5. One primary camera move per shot

Do not stack three camera moves in a 5-second clip. Pick one dominant move (dolly-in, pan, tracking, static). Layer a subtle micro-adjustment if needed (slight handheld shake, gentle rack focus). More than that produces visual chaos.

## 7. U6. Precise lens language

State the lens. "Shot on 50mm" works across all major models. Quick map:

- 24mm. wide, immersive, exaggerated space
- 35mm. natural documentary
- 50mm. intimate, human perspective
- 85mm. portrait, compressed background
- 100mm macro. texture, detail
- anamorphic 40mm. cinematic widescreen

Full vocabulary in `camera-lighting-vocabulary.md`.

## 8. U7. Character consistency anchor

Anchor identity at the START of every prompt. In a multi-clip sequence, repeat the full identity block in every single prompt. Video generators have no memory between generations. Treat every clip like briefing a brilliant intern with memory damage.

Identity block must include: face shape, eye color, skin tone. Hair color, length, style. Facial hair. Exact clothing items. Distinctive accessories.

Model-specific syntax for character locking:
- Seedance: `@img1` reference + identity block (see `seedance.md` §10)
- Kling 1.x – 2.x: Element Binding with 3-4 reference images (see `kling.md` §7)
- Kling 3.0: in-prompt `[Character A: <full identity>]` labels, optionally combined with Element Library (see `kling.md` §3)
- Veo: reference ingredients / JSON identity (see `veo.md`)

## 9. U8. No contradictions

The model obeys the strongest signal. Contradictions produce artifacts.

- Bad. "Still pond" + "flowing water."
- Bad. "Close-up" + "wide cinematic landscape."
- Bad. "Quiet moment" + "explosive action."

## 10. U9. Concrete physical detail over abstract concept

"Loneliness" does not render. "A man sitting alone, shoulders collapsed, face lit by blue phone glow, empty bottles on the table" does.

This is the same rule as the Details Law in section 1, viewed from a different angle. Section 1 is the audit. This is the principle.

Corollary — **consequence prompting**. Current models render real physics, so describe the consequence of an action, not just the action: tires kick up water curtains; the hand grips the jar and the lid actually unscrews; the impact shatters the surface into a spider-web pattern. Action chains where each step forces the next also work as QA — a broken chain exposes a failed generation at a glance.

## 11. U10. Duration discipline

Most models work in 5-10 second clips. Longer narratives live in multiple clips stitched in the editor. Do not cram a 30-second story into a 5-second prompt.

Default splits:

- 10s = 2 clips × 5s
- 15s = 3 × 5s
- 30s = 6 × 5s
- 60s = 12 × 5s

Three exceptions:
- Seedance — 2-3 shots inside one 5-10s clip via "Cut to" syntax (see `seedance.md` §8).
- Kling 3.0 — up to 6 shots inside one generation, up to 15s, with native audio and dialogue (see `kling.md` §3).
- Seedance 2.5 — up to 30s in one pass. The working structure is consecutive stages, each with one primary state change and an explicit visible end state (see `seedance-25.md` §6).

## 12. U11. The final image rule

Every clip needs a clear final frame. The model uses the ending as emotional destination.

- "Ends on his face frozen in the blue refrigerator light" beats "he stands there sadly."

The final image is also one of the five anchors (see `dramaturgy.md` §13). Naming it is non-negotiable.

## 13. U12. The three-detail check (audit before sending)

Before returning the final prompt to the user, audit every shot. Each shot must carry at least one of each:

1. Environmental pressure (lighting, weather, surface, sound of the room).
2. Physical micro-action on the body (jaw, hand, breath, eye, gesture).
3. Sound anchor or recurring visual motif tied to the emotional spine.

If a shot has zero, fix it before sending. If a shot has only one, ask whether you can make it two without bloat. The strongest prompts in this skill's worked examples always have all three.

Empty descriptors that fail this check: "establishing wide shot", "beautiful lighting", "dynamic camera move", "cinematic look", "intense moment", "dramatic close-up". Replace each with three concrete physical facts.

## 14. U13. Reference role discipline

Wherever a model accepts reference assets (Seedance `@Image/@Video/@Audio`, Kling Element Binding and Omni references, Veo ingredients), **every asset gets an explicit role written in the prompt**: what it defines (appearance, motion, voice, scene, camera path) and what to ignore ("Do not use the image background", "Do not use the people in the image").

- Bind each subject individually: "<Character A> corresponds to @Image 1 — use only the appearance, hairstyle, and clothing." Never the collective form "@Images 1 through 4 define four characters respectively" — it does not state which is which.
- Do not restate what a reference already defines. If a video reference carries the motion, name only the attributes to inherit; re-describing every action fights the reference.
- More assets is not more control. Control comes from role clarity; unassigned assets bleed into the frame.

Model-specific limits and templates live in the model files (`seedance-25.md` §5 has the fullest system).

## 15. U14. Priority declaration

When a prompt is overloaded (10+ scenes, many subjects, spatial tricks), adding more description makes it worse. Instead, declare priorities — the model cannot know what matters most unless told what to protect and what to sacrifice:

1. The core subject that must survive every shot.
2. The key shots that must appear.
3. The transitions where the model may freestyle.
4. The mandatory final frame.

This ranks above prompt-length discipline: a shorter prompt with declared priorities beats a longer one without them.

---

*Author: Serge Shima ([t.me/aimastersme](https://t.me/aimastersme) · [sergeshima.com](https://sergeshima.com) · [aimasters.me](https://aimasters.me)) · License: CC BY 4.0 — attribution required · Source: [smixs/visual-skills](https://github.com/smixs/visual-skills)*