higgsfield-seedance

name: higgsfield-seedance description: "Rewrites scene descriptions using professional cinematography language, structures prompts with a six-slot formula (camera + subject + action + setting + style + lighting), and diagnoses content filter rejections via a preflight linter. Use whenever the user asks for a Seedance 2.0 / Seedance Pro prompt, describes a scene for Seedance generation, mentions Seedance, reports a Seedance generation failure or flagged prompt, or is burning credits on Seedance regenerations." user-invocable: true metadata: tags: [higgsfield, seedance, seedance-2.0, seedance-pro, content-filter, prompt, director, flagged] version: 1.8.1 updated: 2026-06-27 parent: higgsfield

Higgsfield Seedance Director

QUICK FACTS

Generated-checked block (build_index.py verifies anchors). Read the linked sections for full context — these lines are routing aids, not the rules themselves.

• The filter is an LLM reading full-scene intent, not a keyword blacklist — describe a SCENE, not a subject; fix the voice first →
• Instant fail (<10s) = filter rejection; delayed fail (>30s) = infra/complexity — never regenerate an instant fail unchanged →
• Six slots, in order: Camera + Subject + Action + Setting + Style + Lighting; missing 3+ slots is where flags come from →
• Empirical prompt-craft laws: 50–80-word attention sweet spot (front-load the load-bearing element), name a director/lens not "cinematic", "fast" degrades motion, no negative prompts in the body →
• Five prompt modes: Reference-Based / Continuation / Expand Shot / Edit Shot / Transformation — pick the mode before writing →
• Hard engine rules (age-blind, exit-frame = cut, off-screen = nonexistent, no reflections, ≤3 tracked characters, double-contrast cuts) + high-risk shot table: ENGINE-RULES.md in this directory
• Reference roles: Character / Last-Frame / Environment / Prop — role determines what the prompt may re-describe →
• Working modes: Exploration / Continuation / Bridging / Repair (distinct from prompt modes) →
• Layer 1 briefing vs Layer 2 production prompt — never paste Layer 1 into the prompt box →
• Native 4K is available in mode=std only; mode=fast (Seedance 2.0 Fast) caps at 480p/720p — in Cinema Studio the model is still capped at 1080p →
• Always preflight: python3 seedance_lint.py --preflight --model seedance_2_0 "<prompt>" — enums come from ../../specs/model-specs.json (fast+1080p/4K and Kling 21:9 are auto-caught) →
• 480p drafts validate the prompt, NOT the take — no seed param; pin Hero Frame + start/end frames to carry a look →
• ZH prompts: hard 1,800-char cap; ZH antislop list enforced by the linter →
• Flagged prompt → rewrite playbook per linter rule, then voice pass →
• Repeated flags → full loop-breaker procedure + LOG THE OUTCOME (--confirmed / add-quality) →

Use this skill whenever the user wants a Seedance 2.0 / Seedance Pro prompt, OR whenever a Seedance generation has been blocked, flagged, or silently failed. This skill's job is to stop credit waste on filter rejections.

Engine rules (read with this file): the hard rendering constraints of the Seedance 2.0 engine — age-blind characters, exit-frame = implicit cut, off-screen = nonexistent, no reflection shots, ≤3 tracked characters, the double-contrast cut rule — live in ENGINE-RULES.md in this directory, together with the high-risk shot table (reflections, same-character doubles, crowds, text rendering) and its mitigations. This SKILL.md is the EN-director profile of that rule core; the ZH-house and bilingual-JSON profiles (../../docs/Seedance 2 Skill.md) obey the same core. Flag high-risk shot types at authoring time — never silently break a rule the project's hero image happens to conflict with.

The Filter Model — Read This First

Seedance 2.0's content filter is not a keyword blacklist. It is a language model that reads the full prompt as a single scene and judges intent and context. Most users burn hours swapping individual words — that loop does not work.

The filter compares two things:

• A prompt that reads like a filmmaker describing a shot → tends to pass.
• A prompt that reads like a note to a friend → tends to fail.

A word that looks sensitive in isolation can sit inside a well-constructed cinematic prompt without issue — the filter reads the full picture. A prompt with no picture to read (no setting, no visual purpose, no narrative logic) gives the filter nothing to work with, and it errs on the side of caution.

Practical rule: the prompt must describe a scene, not a subject. Fix the voice first, then fix the words.

Instant Fail vs. Delayed Fail — the Diagnostic

This single heuristic saves time on every failure:

If the user is seeing instant fails in a loop, it is a filter issue — never a GPU issue. Stop them from regenerating before the rewrite.

The Seedance Prompt Formula

Every Seedance prompt should hit these six slots, in this order:

[Camera movement] + [Subject] + [Action] + [Setting] + [Style] + [Lighting]

All six are technically optional — but a prompt that includes all six almost never gets flagged, because the filter has full context to interpret every word. A prompt missing 3+ slots is where flags come from.

Minimum viable Seedance prompt

Slow dolly-in on a figure in a dark overcoat standing alone at the end of a rain-slick alley. Cold teal shadows, single practical streetlamp, shallow depth of field.

Camera ✓ Subject ✓ Action ✓ Setting ✓ Style ✓ Lighting ✓ — all six slots, ~30 words, passes the filter because the scene is fully legible.

Prompt-Craft Laws

A set of Seedance-2.0-specific prompt rules. These are empirical — practitioner A/B findings that are plausible given the architecture but are not in the official model spec. Treat them as strong heuristics and let the repo's iteration discipline (../higgsfield-prompt/SKILL.md § The Iteration Rule) confirm them on your own material, rather than as guaranteed model behavior.

Length and order — the attention model

Seedance reads the prompt left-to-right with diminishing attention weight. The first sentence carries the most influence; by the third sentence you are in "detail territory," where the model stops treating elements as primary instructions and starts sampling them diffusely.

• Sweet spot: 50–80 words. A 70-word prompt reliably outperforms a structurally identical 200-word version of the same scene — more words past ~3 sentences buys diffusion, not control.
• Structure in three sentences: ① subject + action, ② camera + style, ③ constraints / positive locks.
• Lead with the single most load-bearing element. When a shot lives on its subject, the subject opens the prompt; when it lives on a camera move, the move opens it.

Relationship to the two length numbers. This 50–80-word figure is the coherence optimum. The >180-word figure in § Pre-flight Linter is a different axis — the filter/encoder risk ceiling (>220 often hard-fails the text encoder). 50–80 is where to sit; ~180 is where it starts to break. They don't conflict.

Relationship to the six-slot formula. The six slots guarantee the filter sees a complete scene (presence). The attention model governs weight (order

• length). Keep all six slots present, but the slot list's camera-first ordering is a completeness checklist, not a mandate to open with the camera word when the shot's identity is the subject.

Name the thing — kill empty adjectives

cinematic, epic, beautiful, high quality, amazing are high-frequency labels attached to an enormous range of training footage — dark thrillers, bright rom-coms, nature docs all read as "cinematic" — so the model samples a broad, diffuse distribution and they move the output toward nothing in particular. Don't just delete the slop word (Voice Rewrite §6) — substitute a named, narrowly-trained referent:

Positive form of ../higgsfield-prompt/SKILL.md § Anti-Slop Vocabulary.

"fast" is the highest-degradation keyword

Combined with complex action or camera movement, fast is the single worst-degrading keyword. The temporal branch already runs multiple high-velocity calculations when motion is layered; fast asks all of them to run at maximum velocity at once. Two competing fast elements jitter; three compound into error that's hard to salvage.

Fix: describe the physics, not the speed. feet striking hard, each stride at full extension, arms pumping at 90 degrees produces the perception of speed with no degradation. One element can carry speed — just not all of them simultaneously. (Same family as Voice Rewrite §3 — describe physics, not emotion.)

No negative prompts in the prompt body

Seedance has no negative-embedding architecture for the prompt text — every token is read as a positive instruction. negative: jitter, bent limbs gets parsed as scene description the model tries to render (noise), not as a constraint, and makes the output worse.

Use positive constraint statements — direct declarations of what must be true:

Face stable. Limbs anatomically natural. Consistent lighting, no flicker.
Body proportions consistent throughout.

Scope: this is about the Seedance prompt body. It does not override the Higgsfield UI's dedicated negative-prompt field (which some image models expose and ../../vocab.md § Composition Vocabulary uses). The same positive-only requirement is already documented for Cinema Studio 3.0 in ../shared/negative-constraints.md.

Already-covered siblings (cross-links, not new rules)

• Compound camera move (dolly in while panning left) → jitter at the transition because the model executes the two vectors in sequence. Use one primary move + one texture modifier (slow dolly in, slightly handheld). Full treatment: FAILURE-MODES.md § Multi-motion camera overload.
• Image-to-video subject drift → re-describing what's already in the source image gives the model two competing inputs for one subject; reconciliation introduces drift. Keep an I2V prompt to motion + camera only. See § Seedance 2.0 Prompt Modes / Reference-Based and ../higgsfield-prompt/SKILL.md (I2V key rule).

Seedance 2.0 Prompt Modes

Seedance 2.0 exposes five generation modes that each take the six-slot formula but apply it to a different starting point. Picking the right mode is upstream of prompt writing — the same sentence will produce different results in different modes, because each mode reads the prompt as a different kind of instruction.

Reference-Based

The prompt builds a scene around a source image that carries the visual identity — character, wardrobe, palette, sometimes composition. The prompt's job is NOT to re-describe what the image already shows; it's to place the subject into a new action, setting, or motion context. This is the workhorse mode for any sequence that needs a consistent character across varied shots.

[Source image role: "as the main character" / "as the starting frame"].
[Action the subject performs]. [Environment and atmosphere if not visible in source].
[Camera movement]. [Lighting cue if different from source].

Continuation

The prompt extends a prior Seedance generation forward in time, picking up at the final frame of the previous clip. Identity, wardrobe, environment, and emotional state all carry over. The prompt should describe what happens NEXT — never what just happened. For the full five-rule construction pattern, see the Continuation Prompt Formula section directly below.

[Continuing from prior clip]. [New action that follows from the last frame].
[Camera direction for the continuation]. [Any state change — light shift, new beat].

Expand Shot

The prompt grows the canvas or spatial extent of an existing frame — pulling the frame boundaries outward to reveal what's beyond the original edges. This is NOT a time extension (that's Continuation) and NOT a zoom-out camera move within the original generation. It rewrites the frame itself to include more scene. Useful for turning a tight composition into a wider establishing shot without regenerating from scratch.

[Source frame reference]. Extend the scene [direction: outward / upward / leftward].
[What appears in the newly revealed area]. [Preserve the original subject/composition].

Edit Shot

The prompt modifies specific elements of an existing generation while everything else stays exactly as it was. Think of it as a targeted patch: change a jacket color, remove a background figure, swap a prop, adjust a facial expression. Identity, camera, composition, and lighting stay locked unless you explicitly name them in the change list. The Keep Rule matters here: always state what to preserve alongside what to change.

Change [specific element] to [new state]. Keep [everything else] unchanged.
[Preserve identity, composition, lighting, and camera behavior from the original.]

Transformation

The prompt describes an explicit state change inside a single clip — the subject, object, or environment visibly becomes something else within the shot's duration. Distinct from Continuation (which extends time across two clips) and from Edit Shot (which modifies a generated clip after the fact). Transformation happens during the generation, in one continuous take. Use it when the shot's core idea is the change itself: a character morphing, an object decaying, a landscape shifting from one season to another. The skeleton below is written for character → character; the same pattern applies to object → object and environment → environment with the relevant noun substituted.

[Subject in starting state — full identity descriptors]. [Triggering moment or
cue]. [Subject mid-transformation — what visibly changes, in observable
physical terms]. [Subject in ending state — new identity descriptors].
[Camera behavior across the change]. [Lighting / palette shift if any].

The transformation must be one continuous arc, not a cut. Describe the intermediate state explicitly — the model needs a midpoint anchor or it will either snap from start to end (looks like a cut) or render an ambiguous blur. Keep the duration short (5–8 seconds is the sweet spot for a single transformation); longer clips drift.

Mode Selection Rule

Reference-Based for new action with an existing character. Continuation for the next beat in time. Expand Shot to widen the frame spatially. Edit Shot to patch specific details. Transformation prompt mode when the shot's core idea is a state change inside a single clip — the change is the content. If you find yourself writing across multiple modes in one prompt — stop, pick one, generate, then use the output as input to the next mode.

Continuation Prompt Formula

When writing a Continuation mode prompt, apply these five rules. Skipping any of them is the most common cause of continuation failures: identity drift across the boundary, re-played actions, environment shifts, and broken emotional through-lines.

The Five Rules

1. Last-frame anchor. Open the prompt with a short description of what the camera sees in the final frame of the prior clip — the pose, the position in frame, where the character is looking. This tells the model where to start rendering from. One sentence is enough.

2. Identity anchor. Paste the character's identity block (the same paragraph you used in the original prompt) verbatim into the continuation prompt. Do not paraphrase it. Do not shorten it. Continuation boundaries are where identity drifts — a verbatim re-paste gives the model no room to reinterpret.

3. Prior clip as secondary memory. Name what just happened in one line — "following the door opening," "after the punch lands," "continuing from her turn toward the window." Do not re-describe the action in detail. One referential phrase, then move on.

4. Immediate continuation. Start the new action on the frame that follows the prior clip's final frame. No time skip, no fade, no implied cut — unless the user has explicitly asked for one. If they want a skip, describe it as a new shot instead.

5. No action repeat. The new prompt must extend, not loop. If the prior clip ended on her drawing her weapon, the continuation does NOT describe her drawing her weapon — it describes what she does with it next. Repeating a described action is what causes the "previous beat replays" symptom.

What Must Carry Over

Across the continuation boundary, preserve: character identity (face, build, distinguishing marks), wardrobe (every garment and accessory), environment (architecture, light quality, color treatment, ambient particulates), and emotional carryover (the state the character was in at the last frame — tense, exhausted, alert — should still read on their body in the opening of the continuation).

For the eight named substrate channels that "emotional carryover" decomposes into, see ../../vocab.md § Emotion as Visible Behavior — Channels.

Example

Prior clip ended on a detective standing in a doorway, rain behind her, glancing over her shoulder. The continuation prompt:

Continuing from the prior clip — the detective framed in the doorway, head
turned, rain behind her. [Identity block verbatim: weathered woman, mid-40s,
short dark hair, charcoal trench coat, leather gloves, tired but alert.]
Following her glance back, she steps fully into the corridor, lets the door
swing shut behind her, and begins walking toward camera. Slow dolly-back
matching her pace. Same cool blue-grey palette, same overhead practical light.
Tense, controlled energy carrying over from the prior clip.

All five rules present: last-frame anchor (framed in the doorway, head turned, rain behind her), identity anchor (bracketed block, verbatim), prior clip as secondary memory ("following her glance back"), immediate continuation (steps fully into the corridor — the next frame action), no action repeat (the glance is referenced, not re-performed).

Working Modes vs Prompt Modes — Two Taxonomies

The Seedance 2.0 Prompt Modes section above names five things the platform exposes: Reference-Based / Continuation / Expand Shot / Edit Shot / Transformation. These are platform mechanisms — different pathways through which Seedance accepts a prompt. The Reference Roles and Working Modes sections below name two adjacent concepts that the platform vocabulary does not surface:

• Working modes — user intent. What you are trying to DO with the craft when you sit down to write the prompt.
• Prompt modes — platform mechanism. Which of the 5 input pathways Seedance accepts the prompt through.
• Reference roles — what each reference inside the prompt represents. A semantic-role layer, distinct from the input-modality use-case patterns catalogued in ../higgsfield-cinema/SKILL.md § @ Reference Patterns for Cinema Studio 3.0 (which lists @Image1 / @Video1 / @Audio1 patterns by scenario, not by semantic role).

These three taxonomies are peers, not hierarchical. A single Seedance shot pulls from all three: a working-mode intent picks a prompt mode; references inside the prompt play specific roles.

The "Continuation" Word Collision

"Continuation" names something in both taxonomies:

• Continuation working mode = user intent — "I am picking up where the previous shot left off."
• Continuation prompt mode = platform mechanism — the specific Seedance input pathway that extends a prior generation forward in time (see the Seedance 2.0 Prompt Modes section above).

A user in Continuation working mode almost always uses Continuation prompt mode — the intent and the mechanism line up. But Bridging working mode can also reach for Continuation prompt mode (when the bridge anchors on the last frame of the upstream shot), and Repair working mode can reach for Continuation prompt mode (when the repair is a re-shoot starting from the same last frame as the failed clip). The names overlap; the meanings don't.

In this skill, section context disambiguates: if the surrounding content is in the Working Modes section, "Continuation" means the intent; if in the Seedance 2.0 Prompt Modes section or the Continuation Prompt Formula section, "Continuation" means the mechanism. If still ambiguous, the longer forms — "Continuation working mode" and "Continuation prompt mode" — are always available.

Working Mode → Prompt Mode Mapping

Not a strict mapping. One working mode routes through one or more prompt modes depending on what the shot needs; the table anchors the typical case without claiming a 1:1 bijection.

Reference Roles

Seedance prompts use references — @Image, @Video, and @Audio — to lock specific properties across shots. Each reference plays one of four roles depending on what it locks. This is a semantic-role taxonomy: what the reference IS FOR in the prompt. It sits alongside (not on top of) the input-modality use-case patterns in ../higgsfield-cinema/SKILL.md § @ Reference Patterns for Cinema Studio 3.0, which catalogs concrete prompt patterns by file type.

If a property has to read consistently across multiple shots, assign it to a reference role. If it only matters for one shot, write it inline.

Character

Locks main-character identity across shots — face, build, distinguishing marks. Almost always an image reference; for highest consistency, use the Soul ID character sheet documented in ../higgsfield-soul/SKILL.md § Character Sheet Creation.

Pattern in a Seedance prompt:

@Image1 as the main character. [Identity block verbatim.] [Action the
subject performs.] ...

Last-Frame

Anchors the start of a new clip to a specific frame from the previous one. The role tells the model where to begin rendering from. Used in Continuation prompt mode and inside Bridging working mode. For the full five-rule construction pattern, see the Continuation Prompt Formula section above.

Pattern in a Seedance prompt:

Continuing from the prior clip — [short description of what the camera
sees in the final frame of the prior clip]. [New action that follows.]

Environment

Locks the world and setting across shots — architecture, light quality, ambient particulates, weather state. The role tells the model the specific space the action takes place in, separate from any character in that space. Pairs with ../higgsfield-cinema/SKILL.md § Location Reference Sheets when the same environment recurs across enough shots to earn a sheet.

Pattern in a Seedance prompt:

@Image1 as the environment. [Subject + action.] [Lighting / atmospheric
cues consistent with the environment reference.]

Prop

Locks specific recurring objects — a hero costume piece, a signature weapon, a branded product, a vehicle that appears across multiple shots. The role tells the model that this specific object — not a generic instance of its category — must read identically across cuts.

Pattern in a Seedance prompt:

@Image1 as the prop. [Subject interacts with the prop.] [Camera
behavior.] [How the prop appears in the new shot — same geometry and
material as the reference.]

Per-Image Role Convention

Reference handles (@Image1, @Image2, @Video1, @Audio1) are assigned by upload order — the first image attached becomes @Image1, the second becomes @Image2, and so on. Production practice locks a stable role assignment per slot, kept identical across every prompt in a shot list, so the team and the model both know which reference carries which property without re-reading the prompt body.

@Audio1 is load-bearing on timing, not just atmosphere: an uploaded audio file is a conditioning input that drives cut timing, camera acceleration, and action pace (beat sync), and a [AUDIO: Xs] script block in the prompt body generates dialogue + SFX + lip-sync. Both, plus the first-15s extraction trap, are documented in ../higgsfield-audio/SKILL.md § Audio as a Conditioning Input. The temporal-compatibility constraint below (a @Video1 camera style must not fight the @Audio1 rhythm) is the audio case of the Load-Bearing Rule.

The slot order is not model-enforced — it is team-side discipline. The payoff is reference-stability across long shot lists: once @Image1 = character for the project, that holds for every prompt, and nobody has to re-check which face the model expects at shot 47.

When a reference conflicts with the prompt text — costume reference shows red, text says blue — resolve it explicitly in the prompt body: @Image2 as costume reference, but recoloured to blue for this shot. Don't let an unresolved conflict reach the model.

Load-Bearing Rule

References support memory, but text defines action. The references in a Seedance prompt carry the persistent properties that read consistently across shots; the prompt text directs what happens in this specific generation. References cannot drive new action; text cannot replace what the references carry. Both layers stay in their lanes.

Sibling formulation of the v3.7.1 camera-side rule ("Prompt wins on action, reference wins on texture and world feel" — see ../higgsfield-camera/SKILL.md § Video Reference — What It Reads, and What It Can't, § Load-Bearing Rule). Same underlying principle from different surfaces. The camera-side rule names the WIN order in case of conflict; the Seedance-side rule names the LANES each side covers.

The same distinction applies one level up — at the prompt-construction workflow, not just inside the prompt. When a Seedance clip lands and you want the next prompt to match its look, screenshot the working frame and upload it to Claude, not to Seedance. Claude needs the visual to write a prompt that matches the look; Seedance receives the resulting text prompt and renders the next clip without the screenshot attached. The screenshot is reference (for the prompt-building model); the text prompt is action (for the generation model).

Frame Coordinate System

Frame Coordinate System locks where subjects, props, and compositional elements sit inside the frame.

Qualitative anchors

Standard film-language position language, machine-readable because it is widely-attested in the training data:

• Horizontal: left third, center, right third
• Vertical: upper third, lower third (centered vertically is the default and rarely needs naming)
• Depth: foreground, midground, background

Percentage notation

Numeric coordinates for cases where the qualitative anchors are not specific enough:

• x-position: 0% (far left frame edge) to 100% (far right frame edge)
• y-position: 0% (top of frame) to 100% (bottom of frame)
• frame occupancy: the percentage of the frame area the subject fills, useful for shot-size pinning (a tight close-up sits near 60-80% occupancy; a wide establishing has the subject below 15%)

Use percentages when qualitative anchors are under-specified — e.g., two characters in the same half of frame.

Pair the two notations

Ship the qualitative anchor and the percentage notation together in the same prompt, not as alternatives. The qualitative term gives the model the film-language hook; the percentage gives it the precision target. Example:

Character A stands in the right third, x-position 70%, y-position
50%, frame occupancy 25%. Character B stands in the left third,
x-position 25%, y-position 55%, frame occupancy 22%.

Not a mathematical guarantee

Frame coordinates are a strong compositional anchor, not a geometric guarantee. The model treats them as directorial intent — the same way a DP reads "right third" on a storyboard — not as pixel-exact targets. Use them alongside the rest of the standard composition vocabulary (over-the-shoulder, eye line, ground contact, headroom, nose room, crossing rule — the last formalized at vocab.md § Composition Vocabulary → Crossing rule) rather than as a substitute for it.

When a coordinate drifts in the output, that is the expected behavior class — the coordinate set the intent; the model rendered to its best-fit interpretation. Adjust the prompt by tightening the qualitative anchor or by adding a contact-point clause (feet on the marked floor mark, right hand resting on the table edge) that physically grounds the position rather than re-specifying the percentage harder.

Spatial Layout Block

A Spatial Layout Block is a named structural unit inside a Seedance prompt that consolidates the spatial-vocabulary fields from § Frame Coordinate System into a single block the model can read as one coherent spatial brief. Where Frame Coordinate System provides the vocabulary, the Spatial Layout Block provides the structure for using it.

Scattered spatial directives force the model to reassemble scene geometry from fragments — and it often picks the wrong reassembly.

What goes in the block

A complete Spatial Layout Block names, per subject in frame:

• Identity — which character/prop/element this is (matches a Reference Role handle when references are present)
• Screen position — qualitative anchor + percentage notation paired per § Frame Coordinate System above
• Depth layer — foreground / midground / background
• Frame occupancy — % of frame area the subject fills
• Body orientation — direction the subject faces (toward camera, away, profile-left, profile-right, three-quarter to camera)
• Contact points — what physical surface or object the subject is grounded against (feet on wet asphalt, back pressed against the wall)

Multi-character blocks add the cross-subject relationships: relative distance, eyeline direction between subjects, screen-left vs screen-right consistency, whether subjects cross the central vertical axis, what occludes what.

When to use a Spatial Layout Block

Three triggers:

1. More than one subject in frame. Two-character work is where the model most often swaps screen positions or crosses the central axis without instruction. A block prevents that.
2. A specific compositional intent that needs to read across shots. When the same blocking must hold for several beats — a character anchored left, another anchored right — the block makes the anchor explicit and re-usable.
3. A failure-mode-prone shot. Door-entry shots, hallway-direction shots, and any shot where the model has been picking the wrong spatial reassembly historically all benefit from a block up front rather than inline spatial fragments.

Shots with a single subject in a clear position rarely need a full block; a single qualitative-plus-percentage anchor inside the Dynamic Description suffices.

Block-and-prompt fit

The Spatial Layout Block sits before the Dynamic Description in the output format (see § Output Format for Seedance Prompts below). It primes the model with full geometry; the Dynamic Description then describes the action that happens inside that geometry.

The block does not replace the six-slot formula — camera, lens, lighting, and shot timing stay in their respective slots.

Working Modes

Working modes is a user-intent layer above the platform mechanism. It names what you are trying to DO when you sit down to write a Seedance prompt — independent of which prompt mode you eventually route through. See the disambiguation section above for the relationship between working modes (intent) and prompt modes (mechanism). The mapping table there shows the typical routes.

Exploration

Open-ended discovery. No prior shot to anchor on; no constraint to match. You're generating to find out what the shot wants to be. Short prompts work here — the model has space to bring its own interpretation. Typically routes through Reference-Based prompt mode (with a single character anchor) or pure text-to-video (no references at all).

Continuation

Picking up where a previous shot left off. The prior clip is the anchor; the new clip continues from its final frame. Working mode and prompt mode line up: Continuation working mode almost always routes through Continuation prompt mode. See the Continuation Prompt Formula section above for the five-rule construction.

Bridging

Connecting two existing shots that don't currently flow. The shots themselves work; the cut between them feels wrong — spatial geography is unclear, or the emotional energy mismatches, or the camera character jumps. Bridging uses references from both ends — the last frame of the upstream shot and the first frame of the downstream shot — to navigate the middle. Typically routes through Continuation prompt mode (when the upstream last-frame is the dominant anchor) or Reference-Based (when both ends carry equal weight). Common reference role configuration: Character + Last-Frame + Environment.

Repair

Fixing a failed shot. Distinct from regenerating with a tweaked prompt — Repair acknowledges that the failed clip is data: it shows you what the model interpreted wrong, and that interpretation needs to be addressed directly. Typically routes through Edit Shot prompt mode (when the failure is local — a wrong jacket color, a missing prop) or a fresh Reference-Based generation with corrective prompt text (when the failure is structural — wrong action beat, drifted identity). Pair with the Iteration Rule in ../higgsfield-prompt/SKILL.md § The Iteration Rule when iterating on the corrective prompt.

Decision Tree — Picking a Working Mode

The mode you reach for is downstream of what you're noticing in your work. Diagnose by symptom, then pick the mode that fits:

The decision tree is symptom-first, not mode-first. The mode is the treatment; the symptom in your work is the diagnostic. If you find yourself reaching for a mode without naming what symptom drove the choice, that's a signal to step back.

Two-Layer Prompt Authoring

A skeleton prompt is not meant to be copied blindly into Seedance and expected to work on its own. A skeleton is a structure — the logic of the prompt, not the finished prompt. That matters most for the Bridging, Continuation, and Repair working modes (see § Working Modes above), because those three tasks depend heavily on context: what happened before, what must follow, and what exactly the shot is supposed to solve.

Each practical skeleton in this workflow has two layers, each with a different audience and a different job.

The Two-Layer Distinction

• Layer 1 — task definition / briefing block. Written for yourself or pasted into a ChatGPT-style assistant before the production prompt is drafted. Explains the actual problem in plain prose: what scene already exists, what the next scene is, what is missing between them, what must remain the same, and what the bridge or repair must achieve. Layer 1 is the planning step — it forces the prompt author to define the problem cleanly before writing the model-facing prompt.

• Layer 2 — production prompt for Seedance. Shorter, cleaner, more execution-oriented. Translates the Layer 1 decision into a model-friendly structure: reference roles declared up front, preservation clauses, the one action, anti-repeat language, camera cue, audio cue. Layer 2 is what gets pasted into the generation field.

The distinction makes the workflow practical. Without Layer 1, bridges fail because the prompt author hasn't decided what the bridge is supposed to solve; continuations restage instead of continuing because the prompt author hasn't named what to preserve; repairs over-shoot because the prompt author hasn't isolated what to change. The two layers exist to prevent those three failure modes by separating the planning step from the execution step.

Bridge Skeleton

The Bridging working mode (see § Working Modes / Bridging above) is the problem-solving mode — the bridge is not generic cinematic filler. Use this skeleton when two scene blocks both work but the connection between them does not.

Layer 1 — bridge briefing block. Named fields:

Scene A ends with:
[final visible state of upstream scene]

Scene B begins with:
[opening visible state of downstream scene]

The missing thing between them is:
[reaction / movement into a new space / prop action /
emotional beat / spatial clarification]

The bridge must preserve:
[same character, same outfit, same location logic,
same emotional residue, same prop continuity]

The bridge must not do:
[no new subplot, no repeat of previous action,
no extra threat, no random spectacle]

The purpose of the bridge is:
[explain the transition / make the cut readable /
carry emotion / reposition the viewer in space]

Layer 2 — bridge production prompt skeleton. Reference roles declared up front, then the bridging clauses:

[Reference roles]
@Image1 = character identity reference
@Image2 = continuity start or location anchor (omit if neither is needed)

This is a bridging shot between the previous beat and the next scene.
Its purpose is continuity, not spectacle.

Keep the same character, same outfit, same space logic, same emotional
carryover, and same prop continuity.
Show one readable action that explains the transition.
Do not repeat the previous action beat.
Do not introduce a new threat or subplot.

Scene: [where the character is in this transition moment]
Bridge action: [one small but meaningful movement or reaction]
Camera: [restrained and readable]
Audio: [live sound only if needed]

A good bridge often looks "small" compared to an action scene but does major structural work. If the Layer 2 prompt produces something that feels too eventful, the Layer 1 briefing's "must not do" clause was probably too thin — revise the briefing, then re-derive the production prompt.

Continuation Skeleton

The Continuation working mode (see § Working Modes / Continuation above) solves a temporal problem, not a connection problem: the next clip must begin directly after the previous clip, not as a new restaging. This skeleton operationalizes the five rules in the Continuation Prompt Formula section above — specifically rule #5, "No action repeat."

Layer 1 — continuation briefing block. Named fields:

The previous clip ends on:
[end pose / camera direction / emotional state /
visible props]

The next clip must begin immediately after that.

Keep:
[identity / body direction / location / emotional
carryover / props]

Change:
[the new beat that begins now]

Do not repeat:
[the previous action phase]

Layer 2 — continuation production prompt skeleton. Three reference roles is the typical configuration:

[Reference roles]
@Image1 = exact last-frame continuity anchor
@Image2 = character identity reference
@Image3 = optional environment or prop continuity reference

Use @Image1 as the exact continuity start anchor.
Keep the same character, same lighting logic, same spatial continuity,
same emotional carryover.
Start immediately after the final frame.
Do not repeat the previous beat.

Scene: [what remains unchanged]
New action: [what starts now]
Camera: [how the viewer reads the continuation]
Audio: [live sound only if needed]

If the result keeps replaying the previous beat, the correction is not "make the prompt longer." The correction is to strengthen the temporal and anti-repeat language. Useful phrase variants:

• start immediately after the final frame
• do not repeat the previous fight
• do not restage the earlier beat
• continue forward into the new action
• preserve the same fatigue state and emotional carryover

These are interchangeable — pick the variant whose verbs match the prior clip's content. A continuation following a fight scene wants "do not repeat the previous fight"; a continuation following a quiet moment wants "do not restage the earlier beat."

Repair Skeleton

The Repair working mode (see § Working Modes / Repair above) does not behave like "generate the scene again, but better." That breaks continuity and changes too much. The real question is always: what exactly am I trying to preserve, and what exactly am I trying to change? A usable repair prompt has two parts that map directly onto that question — a preservation block and a modification block.

Layer 1 — repair briefing block. Named fields:

Current clip / image state:
[what already works and must remain stable]

The exact problem:
[what is wrong]

Preserve:
[identity / framing / pacing / space / continuity /
lighting / emotion / prop logic]

Change only:
[one or two specific elements]

Do not damage:
[what tends to drift if the edit is too broad]

Layer 2 — repair production prompt skeleton. Tight, surgical, no descriptive ornament:

Keep the original framing, pacing, environment, and character
identity.
Preserve the same outfit, same lighting logic, same scene layout,
same emotional state.
Change only [the exact element that needs fixing].
Do not alter the rest of the shot.

The "do not damage" field in Layer 1 is the field most often skipped and most often the source of repair failures. Name the properties that typically drift when an edit goes too broad — those are the properties the model needs explicit protection on, even if they aren't the properties the edit is targeting.

Keyframe Workflow

The most useful official direction on fine-grained Seedance editing comes from BytePlus VideoPilot — Seedance's official editing-style interface from ByteDance / BytePlus. VideoPilot frames fine-grained video editing not as one vague "fix this clip" prompt but as a reference + keyframe + local modification workflow. Three named ingredients, each with its own job.

This section names what VideoPilot's interface exposes (Capability Surface), how to translate those primitives into prompt-only Seedance work when the dedicated UI isn't in play (Translating to Seedance Prompts), and the underlying mindset that makes the whole approach work (The Editor-not-Regenerator Mindset).

Sourcing: The keyframe-editing capability surface below is from the BytePlus VideoPilot fine-tuning documentation (docs.byteplus.com) and ByteDance's official Seedance launch materials (seed.bytedance.com). Same official source set as the Rule of 12 citation at ../higgsfield-models/MODELS-DEEP-REFERENCE.md:274.

Capability Surface

VideoPilot exposes five named editing primitives. These are what the official UI lets you do; the prompt-side translation in the next section is the closest equivalent when working through prompts alone.

• Continuous keyframe segmentation. VideoPilot parses a reference video into continuous keyframe segments. The segmentation is done by the system, not assembled by hand. The unit of edit is the keyframe, not the whole clip.

• Fine-grained keyframe edits. Edits target a single keyframe at a time. Surgical at the temporal axis — change one frame's content without rewriting any other frame's instruction.

• Custom keyframes. The editor can add keyframes the system didn't auto-detect. Useful when an important beat falls between the auto-segmented keyframes.

• Partial redraw of selected regions. Spatial-local edits within a keyframe — mask the region, redraw only what is inside the mask. Surgical at the spatial axis (vs. the temporal-axis surgery of fine-grained keyframe edits).

• Keyframe description rewrite. Rewriting the description of one keyframe causes the system to regenerate that frame AND its transition logic to neighboring keyframes accordingly. This is the closest official primitive to Seedance's Edit Shot prompt mode (see § Seedance 2.0 Prompt Modes / Edit Shot above).

Translating to Seedance Prompts

When working through prompts and references rather than the dedicated VideoPilot keyframe UI, the closest practical equivalent is six operational rules. None of them guarantee perfect surgical editing in every interface — they translate the official editing workflow into prompt-based use.

1. Use a screenshot or final frame as your stability anchor.
2. Keep the identity reference separate from the continuity anchor.
3. State exactly what must remain unchanged.
4. State exactly what is changing.
5. Forbid repetition of the previous beat if this is a continuation.
6. If the edit is local, describe only the local change and explicitly protect the rest.

These map onto existing repo surfaces: rules 3, 4, and 6 onto the Repair Skeleton's preserve / change blocks (see § Two-Layer Prompt Authoring / Repair Skeleton above); rules 1 and 2 onto the Reference Roles taxonomy (see § Reference Roles / Last-Frame and § Reference Roles / Character above); rule 5 onto the Continuation Skeleton's anti-repeat phrase library (see § Two-Layer Prompt Authoring / Continuation Skeleton above).

The Editor-not-Regenerator Mindset

The conceptual root of the whole keyframe workflow surface: if the goal is surgical edits, think like an editor, not a full regenerator. Freeze the parts that must remain stable. Isolate the parts that must change. Then make the instruction local and explicit.

This is also the conceptual root of the Repair Skeleton: the preserve / change split is the prompt-side enactment of the editor-not-regenerator stance, the same discipline VideoPilot's UI primitives express at the interface level.

Pre-flight Linter

Before the user generates, run the prompt through the full preflight:

python3 seedance_lint.py --preflight --model seedance_2_0 "<prompt text>"

The linter is at the project root (seedance_lint.py). --preflight chains three passes into one PASS/WARN/FAIL report:

1. Filter lint (always on):

• Real names of public figures / celebrities / politicians
• Brand, IP, franchise names (Nike, Marvel, Spider-Man, Pokémon, etc.)
• Raw violence verbs (fight, attack, kill, shoot, blood, gore, stab)
• Age markers (child, kid, young, teen, boy, girl — Seedance is age-blind)
• Note-to-friend voice (no Style/Mood, no Camera, no Lighting sections)
• Overlength (>180 words is risk territory; >220 words often hard-fails on the text encoder, not the filter)
• Conflicting instructions (moving + frozen, bright + dark, etc.)

2. Structural lint (with --model <id>; driven by ../../specs/model-specs.json, never guessed) — the expensive failure class:

• Declared shot count ("strictly N shots" / 严格N个镜头) vs actual 【镜头N】/[Shot N] block count
• Timed beats ([0-4s]) summing past the declared duration / model max
• ZH prompts over the 1,800-character hard cap; ZH antislop phrases
• @handle used before its declaration line
• Aspect ratio / resolution / mode / duration outside the model's enum — catches Seedance fast+1080p (fast cannot output 1080p) and Kling 3.0
  • 21:9 (no native 21:9)

Settings are read from the prompt's own header lines (**Aspect ratio**: …, Resolution: …, mode: …, Duration: Ns); override per-field with --ar / --resolution / --mode / --duration.

3. Memory recall: the most relevant past failures from ../../db/filter-memory.json / ../../db/quality-memory.json surface as INFO notes.

Output is PASS, WARN, or FAIL with the specific fix for each rule hit. Treat FAIL as "do not hit generate." Treat WARN as "likely to pass, but here is what to harden." Exit codes: 0 pass/warn, 1 fail, 2 usage — safe to script.

Drafts Validate the Prompt, Not the Take

The 480p tier is for prompt iteration, not take approval. Seedance 2.0 exposes no seed parameter (verified — ../../specs/model-specs.yaml lists resolution, mode, genre and nothing else), so re-running an approved 480p draft at 1080p is a fresh roll: a new performance, a new camera micro-trajectory, new timing. "Approve cheap, re-render at quality" is not a workflow Seedance supports.

To carry a look you approved into the final render, use the documented transfer mechanism: the Hero Frame (../higgsfield-assist/SKILL.md) plus start/end-frame pinning (start_image / end_image reference roles — see § Reference Roles above). Pin the frame, not the roll. Fine-detail judgments must be re-checked at final resolution — 480p hides exactly the detail they're about.

The Rewrite Playbook

When the linter fires, apply the substitutions below. These are drawn from ../../db/filter-memory.json — every pattern here has been confirmed to work on past flagged prompts.

Real names → archetype description

❌ "Keanu Reeves walking into a boardroom" ✅ "A lean man in his late 50s, dark shoulder-length hair, stubble, intense calm expression, in a dark suit, walking into a modern glass boardroom"

Brand / IP → visual attributes only

❌ "Spider-Man swinging through New York" ✅ "A figure in a red and blue form-fitting suit, masked, swinging between skyscrapers on a tensile white line"

❌ "Nike shoes on a running track" ✅ "White athletic shoes with a dark swoosh-free silhouette on a red rubber running track"

Violence → aftermath / tension / physics

❌ "Two people fighting in an alley" ✅ "Two figures locked in a tense physical confrontation, rain-slick alley, dramatic low-key lighting, camera shuddering on each impact"

❌ "An explosion destroys the car" ✅ "A burst of orange light and smoke billowing out from the car, metal buckling outward, glass fragments catching the light"

❌ "Blood drips from his hands" ✅ "His hands tremble at his sides, something dark staining his cuffs"

Weapon → prop + purpose

❌ "A man holds a gun to another man's head" ✅ "A standoff in a concrete stairwell — one figure's arm extended, the other perfectly still, both silhouettes hard-edged against a single overhead fluorescent"

Horror / dark → atmosphere, not acts

❌ "A monster tears a victim apart" ✅ "The aftermath of something wrong — an empty room, overturned furniture, a single smear trailing toward the door, ambient dread, flickering practical lamp"

Voice Rewrite — the "Filmmaker not Friend" Pass

Even with every risk token removed, prompts still get flagged if the voice is wrong. Do this pass on every Seedance prompt:

1. Add a Style & Mood clause up front. Palette, lens, lighting, atmosphere. Never skip this. It tells the filter "this is a shot."
2. Name the camera move. "Slow dolly-in," "low-angle tracking," "static medium." Not "the camera moves forward."
3. Describe physics, not emotion. "Jaw clenches, nostrils flare" not "looks angry." The filter reads physics as cinematic; emotion language as ambiguous intent. For the muscle-level extreme of this rule — facial expressions as FACS Action Unit codes (AU4+AU5+AU7 for anger) in close-up and dialogue — see ../higgsfield-facs/SKILL.md.
4. Describe force and direction, not destruction sequence. "Driven into the car, metal buckling" not "thrown into side door, glass shatters, uses rebound to sweep leg."
5. Present tense, active voice. "She turns" not "she is turning."
6. Cut the antislop words. Breathtaking, stunning, epic, masterfully, cinematic masterpiece — these signal marketing copy, not a shot description, and correlate with flags.

For the eight named substrate channels that "describe physics, not emotion" decomposes into, see ../../vocab.md § Emotion as Visible Behavior — Channels.

Output Format for Seedance Prompts

When generating a Seedance prompt for the user, use this structure. It mirrors what Seedance's filter reads most cleanly:

**Model:** Seedance 2.0
**Aspect ratio:** 16:9   **Duration:** 10s

**Style & Mood:** [palette, lens, lighting, atmosphere — 1 sentence]

**Dynamic Description:** [camera move + subject + action, present tense,
shot-by-shot if multi-cut. This is the main block.]

**Static Description:** [location, props, ambient details — 1-2 sentences]

**Camera:** [exact movement name]

For the full bilingual EN+ZH director output format (used in Seedance's web UI), see the extended reference at ../../docs/Seedance 2 Skill.md.

Runtime arithmetic for multi-shot prompts

Runtime appears in three places in a delivered Seedance prompt — the title line, the meta header (**Duration:** Xs), and any per-shot timing labels in the Dynamic Description. All three must agree.

For multi-shot prompts, label each shot inline with its time range (e.g. Shot 1 (0-3s): ... hard cut to Shot 2 (3-8s): ... hard cut to Shot 3 (8-15s): ...). The per-shot labels must sum to the total duration stated in the title and meta header; a drift between the two surfaces is the most common source of "my multi-shot prompt rendered as a single shot" failures.

Always ask the user for runtime — never default. A 5s, 10s, or 15s assumption silently degrades adherence on prompts that needed a different cap.

Shot density for multi-scene prompts

When grouping multiple shot rows into a single Seedance prompt (rather than splitting into separate prompts), use this starting heuristic: roughly one prompt per 4-5 shot rows. The heuristic is project-derived empirical observation, not platform-enforced, and varies wildly by scene type.

Group shot rows into one prompt when ALL of these hold:

• Same character set in frame
• Same location or contiguous subset of a location
• Continuous emotional / temporal unit (no time skip, no major mood pivot)
• Combined runtime fits within the 15s Seedance cap
• The grouped prompt text stays within practical generation limits (~2500 characters)

Split into separate prompts when any of these fire: hard cut between locations (e.g. apartment → flashback), major character entrance or exit changes the handle list, or the combined runtime exceeds 15s.

The heuristic is a starting state, not a target. Adjust per project as you learn how Seedance handles your particular scene-type density — dense action sequences may want 1 prompt per 2-3 shot rows; quiet emotional scenes may collapse to 1 prompt per 8+ rows.

Single-vs-multi-shot decision

Default is single-shot. Reach for multi-shot when the content is action, dynamic dialogue, or anywhere a cut is itself doing work a single shot cannot deliver. Everything else holds tighter as a single continuous shot.

For single-shot continuous motion, per-second beats give fine-grained control without provoking cuts — [0-3s] subject enters frame, [3-7s] camera pushes in. The bracket-notation reference lives in ../../vocab.md § Editing Syntax (shipping in v3.7.7 sub-phase 2f).

For multi-shot, use the Runtime arithmetic above — each cut labeled with its time range, sum equals total duration. Action scenes earn an extra layer: per cut, name the participants, location, implements, and beat-by-beat choreography.

Anti-pattern: per-3-second time labels written inside what was meant as a single continuous shot. Seedance reads any per-segment timing block as cut instructions and inserts cuts. Pick a side — if you want continuity, drop the time markers; if you want cuts, label them with Shot 1 / Shot 2 / Shot 3 and the multi-shot arithmetic above.

Post-Clip Decisions

When a generated clip raises questions around itself, testing becomes narrative work — not "is it good?" but "what does it do?" and "what comes after?" The diagnostic below asks four scene-function questions; the decision tree maps the answers to next-shot types.

The Four Questions

After any strong clip, ask these four in order. They surface what the clip is doing in the episode and what should come next.

1. What function does this scene have?
2. What is missing for it to feel connected?
3. What shot would make the connection readable?
4. Is the next step continuation, bridge, contrast, or reset?

These questions are scoped to the next move, not to "solving the whole episode." The narrower scope is what keeps them practical.

Next-Shot Decision Tree

The right question is not "what is the coolest next shot?" but "what problem does the episode have right now?" Map the problem to a shot type:

• Strong but isolated → continuation or before/after
• Two scenes do not connect → bridge
• Spatial logic unclear → geography clarification
• Structure works but feeling weak → close-up or reaction insert
• Something broken → targeted repair

The next shot is chosen by function, not by excitement.

Note: "continuation," "bridge," and "targeted repair" here name next-shot types decided post-generation. "Continuation," "Bridging," and "Repair" in § Working Modes above name per-clip intent during composition — different lifecycle phase, different decision.

When the User Is Already in a Failure Loop

This section handles filter rejections — prompts the Seedance filter blocks before generation. For render failures (FPS drift, NSFW false-positive, keyframe-invention, physics-state drift, spatial- awareness failures, multi-motion overload), see FAILURE-MODES.md in this directory — sibling catalog with symptom + mechanism + counter per named failure.

If the user tells you Seedance has flagged them multiple times in a row:

1. Ask for the exact prompt text that got flagged. Don't guess.
2. Run the preflight linter on that exact text.
3. Apply the rewrite playbook for every rule the linter hit.
4. Do a voice pass (add Style & Mood, name the camera, present-tense physics).
5. Log the outcome to the learning memory so future sessions benefit. These are concrete steps, not optional polish — the memory system only learns if outcomes actually get written:
   • After a rewrite passes Seedance's filter in a real generation, log it as a confirmed workaround: python3 seedance_lint.py --confirmed "<the prompt that passed>"
   • If you logged a predicted rejection earlier (--log) and later learn the outcome: python3 higgsfield_memory.py update-filter <id> <fixed|workaround|still-blocked>
   • After a quality fix is confirmed (motion, identity, blocking — not a filter issue): python3 higgsfield_memory.py add-quality '<json entry>' with the original prompt, the failure description, and the improved prompt.
   • For production-specific lessons that shouldn't pollute global memory, add --project <name> (entries land in ../../db/projects/).

Do not let the user regenerate the same prompt with one word changed. That is the loop that wastes hours.

Multi-Language Prompt Workarounds

Seedance prompts default to English. This section documents historical language-level workarounds for specific Seedance platform states.

Chinese (as of 2026-05-17)

At Seedance 2.0's launch the model performed better against Chinese prompts and enforced a hard 3,000-character cap per prompt. English runs roughly 5-10 characters per word; Chinese runs 1-2. Production teams used Chinese prompts to compress ~5× more directive content into the same character budget — the decisive workaround on long multi-shot prompts that otherwise hit the cap.

The workaround was a launch-window optimization, not a permanent convention. If a long Seedance prompt keeps hitting the cap and English compression has been exhausted, the Chinese-density path has shipped before — verify the cap state in the current Seedance UI before reaching for it.

Related Skills

• higgsfield-prompt — MCSLA formula, archetype router, general prompt structure; the Iteration Rule and 6-Pass Diagnostic Sequence for when generations are off-target and you can't name why
• higgsfield-troubleshoot — diagnosis for non-filter failures (render quality, etc.)
• higgsfield-recall — pre-generation memory check against past failures
• ../shared/negative-constraints.md — full negative-constraint reference, including the Content Filter / Safety section
• ../../docs/Seedance 2 Skill.md — extended bilingual director reference (archetypes, cut rules, camera language appendix)