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":"1.14.0","updated":"2026-08-22T00:00:00.000Z","parent":"higgsfield"} Higgsfield Seedance Director QUICK FACTS Generated-checked block (scripts/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, unidirectional motion chains + named camera endpoint + detail scale follows shot size → Five prompt modes: Reference-Based / Continuation / Expand Shot / Edit Shot / Transformation — pick the mode before writing → [OFFICIAL] block scaffold for production prompts: SCENE CONTEXT → … → POSITIVE LOCKS, distributed style on standalone briefs (connected shotlists glue the compiled Style Prefix verbatim instead), FOV in degrees only, CAMERA block 3rd, cut ladder oner / CUT n / timed / freestyle → [FIELD] 13-project corpus calibration: word length scales with register (218w → 2,059w medians — the 50–80w sweet spot is single-shot-only), video briefs hand-authored ( enhance_prompt off), Style Prefix = per-project constant compiled into home blocks → [FIELD] Three "helpful-instinct" drift sources, each with a standing lock: environment invention (#1, above character drift), character-height equalization, scale drift on wides → Build-safe construction for crowds/destruction/creatures: evacuated cities, contained fights ("stays at the sea surface"), the safe benchmark scene → Extend an existing clip: attach it as a video reference + open with "The scene continues." — match source resolution AND duration; chain cap ~2 (hard 3), then re-anchor from ORIGINAL references → This file is Seedance 2.0. For 2.5 — four modes incl. video_edit / video_extension , 4–30s, 30/10/10 references, in-prompt first-last frames, 720p ceiling — use ../higgsfield-seedance-2-5/SKILL.md Tutorial-demonstrated patterns (reference-role vocabulary incl. VARIETY reference, SCREEN REALISM + duration-match composites, 60:30:10 grade, red-arrow prop annotation): PRODUCTION-PATTERNS.md in this directory [OFFICIAL] Feature-film pipeline (asset construction, per-scene GEO SPATIAL LAYOUT, the position-fixing first second, dialogue construction, ban dictionary, the 10–15 iteration rule, crowds / giants / thresholds): HELL-GRIND.md in this directory Performance — objective, obstacle, tactics, beats, subtext, eye life, the acting master profile: ../higgsfield-acting/SKILL.md 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 scripts/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. Production patterns (sibling reference): patterns demonstrated working in Higgsfield's own Seedance-4K film tutorial — reference-role vocabulary, coordinate blocking, video-reference screen composites, prompted imperfection, 60:30:10 grade — live in PRODUCTION-PATTERNS.md in this directory, labeled [DEMO] . 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: Failure timing Meaning What to do < 10 seconds (instant) Content filter rejection — prompt never reached the GPU Rewrite for voice + remove risk tokens. Do not regenerate unchanged. > 30 seconds (delayed) Infrastructure, timeout, or complexity — prompt passed the filter but the render failed Simplify action density, cut length, try again 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 (short-form regime). 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. (Block-scaffold production prompts are the other regime: § Official Prompt Architecture.) 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 : Empty adjective Named substitute (samples a narrow distribution) "cinematic" / "epic look" a director : "Wes Anderson symmetry" (centered framing, pastel) · "Kubrick one-point perspective" (geometric corridors) "cinematic lighting" a lighting setup : "golden-hour backlight, long shadows stretching forward" "beautiful" / "high quality" a lens spec : "anamorphic 2.39:1, lens flare from a practical light source" Positive form of ../higgsfield-prompt/SKILL.md § Anti-Slop Vocabulary. Official override on director names. Higgsfield's own prompt-writing skill forbids director names, signature-work references, and equipment model names outright (see § Official Prompt Architecture — the Block Scaffold → Measurable-language rules). The director-substitute trick above is an empirical short-form fallback; in block-scaffold prompts, describe the look in observable terms instead — "centered symmetrical framing, pastel palette", not "Wes Anderson symmetry". "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 , and the target is negative: list syntax / bare negation lists — not every "no" token. A short lock tail inside a positive declaration ("Consistent lighting, no flicker"; the Style Prefix's "Photorealistic — no 3D render") is fine and field-proven across the harvest corpus. 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 . Ambiguous verbs — the homograph trap (v1.10, Peter's find 2026-07-14) If a word has a plausible second reading, Seedance may take it. The observed case: "wind tearing at her coat" — meant as fabric pulled violently; the model sometimes reads tearing as ripping (fabric shredding) or tearing up (crying), and the shot changes accordingly. This is not covered by any known prompt guide — treat it as a first-class law: Before a verb ships, ask: is there a second physical thing this word can look like? If yes, replace it with the phrasing only ONE thing can look like. wind tearing at her coat → wind whipping violently at her coat / her coat flutters violently in the wind Seed homograph list (grow it whenever a generation misreads a word): tearing (rip / cry) · shoot (fire / film) · duck (crouch / bird) · bolt (run / lightning / hardware) · draw (pull / sketch / weapon) · wave (hand / ocean) · charge (run at / electricity) · rock (sway / stone) · drop (fall / droplet) · fire (flame / shoot / dismiss) · strike (hit / match / lightning) · break (shatter / pause / dawn) · pound (hammer / heartbeat) · snap (break / photo / fingers). The list is a seed, not the rule — the rule is the self-check, which generalizes to any word forever. Community v3 cherry-picks (Joey drop, audited 2026-07-14) Adopted (genuinely absent from this skill until now): Camera on the shadow side, with a stated operator axis. Place the camera on the shadow side of the key light and say where the operator stands/moves — light wraps toward the lens and faces keep dimension. Detail-on-wide ("snake cam"). 84° low-angle placed hard against a small foreground object — detail-shot intimacy without losing the wide's context. Intimate wide. 63–84° on a close face instead of a long lens — presence without compression; the room stays in the frame. Prompt-reset heuristic. When iterations are getting worse , stop stacking fixes: strip the prompt back to subject + action + camera and re-add only what's necessary. Density is a bell curve; past the peak you can't tell which element the model dropped. Canonical-over-plate. Every subject keeps its own identity reference even when it is visible in the environment plate — the plate carries the world, the canonical ref carries identity; never let a plate double as an identity source. Contrast curve stated three ways. When the grade matters, state it as tonal curve + specular removal + named grade — one phrasing alone drifts. Rejected (was: flagged, test day pending): their worldbuilder puts the camera block at the BOTTOM ("at the top FOV fights identity data") — this contradicts both this skill's CAMERA-3rd-position rule and their own seedance skill. Resolved 2026-07-26 by field evidence instead of a test day [FIELD — 13-project community harvest] : across ~4,000 harvested production prompts from 9 creators, the CAMERA block sits mid-document in every final prompt — never at the bottom. CAMERA-3rd stands; the bottom-position claim is dropped. Motion-prompt laws (dramaclaw production corpus, audited 2026-08-09) [EMPIRICAL — dramaclaw production corpus, Seedance] — practitioner findings earned in dramaclaw's Seedance production work. The craft is model-agnostic i2v motion-writing rather than a Seedance spec; same epistemic status as the rest of this section (strong heuristics — confirm on your own material). Unidirectional motion only. A short action that finishes early leaves the model with seconds of clip to fill, and it fills them by reversing the action — the character walks forward then steps back, leans in then pulls away. Chain 2–3 connected actions in the same direction so the motion spends the whole clip; a deliberate there-and-back is two shots , never one prompt. (Failure face: FAILURE-MODES.md § Action-reversal fill.) Name the camera endpoint. A camera move needs a destination, not just a name — say what the frame shows when the move finishes ("slow dolly-in, ending on her hands wrapped around the cup"), not only the move's name. A move that runs out of instruction before it runs out of clip drifts or reverses — the camera face of the unidirectional law. Detail scale follows shot size. Close-ups earn micro-detail (fingers tightening, a jaw flex); wides earn broad arcs (crossing the courtyard, the crowd parting). Cross-matching — micro-detail written into a wide, or a broad traversal written into a close-up — is unrenderable at that shot size and degrades the whole clip. (Detail inside a wide is a composition problem, not a prompt-detail problem — see the snake-cam cherry-pick above.) 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). Official Prompt Architecture — the Block Scaffold