Scroll Promo Site Builder
kangarooking/kangarooking-skills
Create a scroll-controlled cinematic product website with rich motion (动效网站) from product materials, reference pages or videos, and brand assets.
Seedance 2.5 prompt director — the omni-reference dialect. An agent skill from OSideMedia/higgsfield-ai-prompt-skill.
$ npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield-seedance-2-5 -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install OSideMedia/higgsfield-ai-prompt-skill higgsfield-seedance-2-5 --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/OSideMedia/higgsfield-ai-prompt-skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/higgsfield-seedance-2-5 .claude/skills/higgsfield-seedance-2-5 && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "higgsfield-seedance-2-5" agent skill from https://github.com/OSideMedia/higgsfield-ai-prompt-skill/tree/main/skills/higgsfield-seedance-2-5 into .claude/skills/higgsfield-seedance-2-5/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "higgsfield-seedance-2-5", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/OSideMedia/higgsfield-ai-prompt-skill/tree/main/skills/higgsfield-seedance-2-5Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield-seedance-2-5 -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install OSideMedia/higgsfield-ai-prompt-skill higgsfield-seedance-2-5 --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OSideMedia/higgsfield-ai-prompt-skill.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/higgsfield-seedance-2-5 .agents/skills/higgsfield-seedance-2-5 && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "higgsfield-seedance-2-5" agent skill from https://github.com/OSideMedia/higgsfield-ai-prompt-skill/tree/main/skills/higgsfield-seedance-2-5 into .agents/skills/higgsfield-seedance-2-5/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "higgsfield-seedance-2-5", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield-seedance-2-5 -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install OSideMedia/higgsfield-ai-prompt-skill higgsfield-seedance-2-5 --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OSideMedia/higgsfield-ai-prompt-skill.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/higgsfield-seedance-2-5 .cursor/skills/higgsfield-seedance-2-5 && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "higgsfield-seedance-2-5" agent skill from https://github.com/OSideMedia/higgsfield-ai-prompt-skill/tree/main/skills/higgsfield-seedance-2-5 into .cursor/skills/higgsfield-seedance-2-5/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "higgsfield-seedance-2-5", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/OSideMedia/higgsfield-ai-prompt-skill.git --path skills/higgsfield-seedance-2-5--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield-seedance-2-5 -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install OSideMedia/higgsfield-ai-prompt-skill higgsfield-seedance-2-5 --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OSideMedia/higgsfield-ai-prompt-skill.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/higgsfield-seedance-2-5 .gemini/skills/higgsfield-seedance-2-5 && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "higgsfield-seedance-2-5" agent skill from https://github.com/OSideMedia/higgsfield-ai-prompt-skill/tree/main/skills/higgsfield-seedance-2-5 into .gemini/skills/higgsfield-seedance-2-5/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "higgsfield-seedance-2-5", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install OSideMedia/higgsfield-ai-prompt-skill higgsfield-seedance-2-5Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield-seedance-2-5 -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/OSideMedia/higgsfield-ai-prompt-skill.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/higgsfield-seedance-2-5 .github/skills/higgsfield-seedance-2-5 && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "higgsfield-seedance-2-5" agent skill from https://github.com/OSideMedia/higgsfield-ai-prompt-skill/tree/main/skills/higgsfield-seedance-2-5 into .github/skills/higgsfield-seedance-2-5/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "higgsfield-seedance-2-5", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield-seedance-2-5 -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install OSideMedia/higgsfield-ai-prompt-skill higgsfield-seedance-2-5 --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OSideMedia/higgsfield-ai-prompt-skill.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/higgsfield-seedance-2-5 .opencode/skills/higgsfield-seedance-2-5 && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "higgsfield-seedance-2-5" agent skill from https://github.com/OSideMedia/higgsfield-ai-prompt-skill/tree/main/skills/higgsfield-seedance-2-5 into .opencode/skills/higgsfield-seedance-2-5/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "higgsfield-seedance-2-5", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
higgsfield-seedance-2-5Seedance 2.5 prompt director — the omni-reference dialect. An agent skill from OSideMedia/higgsfield-ai-prompt-skill.
Higgsfield Seedance 2 5 is an agent skill from OSideMedia/higgsfield-ai-prompt-skill. Seedance 2.5 prompt director — the omni-reference dialect. Routes the four generation modes (t2v / omnireference / videoedit / videoextension), writes explicit @Image/@Video/@Audio reference roles with exclusions, stages 30-second videos into end-state beats, and covers video editing, forward/backward extension, first-last-frame and multi-keyframe control, storyboard grids, blockout rendering, and seamless transitions. Use whenever the user asks for a Seedance 2.5 prompt, mentions Seedance 2.5 / Dreamina /…
Its SKILL.md is about 11k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `MODE-PLAYBOOKS.md` and `VFX-PIPELINE.md`).
It sits in Media & Creative, covering AI video generation and Video production. It works with Seedance. The repository describes itself as: Claude AI skill for cinematic Higgsfield AI prompts — 32 sub-skills covering Seedance 2.5 (omni-reference, video edit + extend) and 2.0, the Hell Grind feature-film pipeline, an… The licence is MIT.
2 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 7075497. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
python3From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Higgsfield Seedance 2 5 loads about 11k tokens when it runs. Until then it costs about 203 tokens; SKILL.md has 5,489 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from OSideMedia/higgsfield-ai-prompt-skill at commit 7075497, republished under its MIT licence (© OSideMedia). 5,489 words, ~11,498 tokens.
.claude/skills/higgsfield-seedance-2-5/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.Seedance 2.5 is a different dialect from Seedance 2.0, not a version bump you can prompt through by habit. 2.0 is a reference-driven shot generator with a 4K lane and a genre hint. 2.5 is an omni-reference production model: up to 50 reference materials, 30-second native runtime, and three non-generation modes — it can edit a video you already have, and extend one forward or backward from its boundary frame.
The prompt grammar changes with it. Reference roles are declared in prose (@Image 1 defines …), audio and text get bracket syntax, long videos are staged with explicit end
states, and first/last frames live inside omni_reference — either as the platform's
start_image / end_image roles or announced inside the prompt — never as a separate
mode.
Model split — read this before writing anything. 2.5 tops out at 1080p (no 4K lane) and has no
genrehint. Since the 2026-09-26 snapshot it does exposestart_image/end_imageroles — but only inomni_referencemode. If the job needs 4K or a genre hint, it is a Seedance 2.0 job —../higgsfield-seedance/SKILL.md. See § Choosing 2.0 vs 2.5.
Generated-checked block (scripts/build_index.py verifies anchors). Routing aids — read the linked sections for the rules themselves.
t2v · omni_reference · video_edit · video_extension; the mode changes what the prompt is →start_image/end_image only in omni_reference, t2v takes zero references, no genre hint, extension_mode required for (and only for) video_extension →video_edit ignores duration and aspect_ratio and bills by the source video's length; video_extension inherits the source's aspect ratio →start_image/end_image counts against both; stability ranges are 1–8 subjects (images), 1–5 subjects at 5–10s (video/audio) →@Images 1 through 4 define four characters is the canonical failure →() music · <> SFX · {} dialogue · 【】 subtitles; non-Chinese dialogue needs a language line before the line; a music suppression never goes inside () — (no music) there reads as a music cue (house inference, the default) →omni_reference work: the platform start_image/end_image roles or an in-prompt declaration (@Image 1 is the first frame) — which holds better is unmeasured; keyframes 3+ are always in the prompt; never merge two anchors into one sentence →MODE-PLAYBOOKS.mdMODE-PLAYBOOKS.mdomni_reference v2v lane (source ≥4s, duration = source), the four-batch rule, the slop catalog: VFX-PIPELINE.md[Age/Race] label →Two primary sources, labelled throughout, plus the secondary sources below. What each
label means — and the evidence it requires — is the repo-wide legend in
../shared/provenance.md.
| Label | Source |
|---|---|
[OFFICIAL — Dreamina] | ByteDance's Dreamina Seedance 2.5 Prompt Guide + User Guide — the model vendor's own prompt doctrine. Prompt grammar is model-side, so it carries across to Higgsfield's hosting. |
[OFFICIAL — platform] | Higgsfield's live models_explore catalog, snapshot 2026-09-26 (../../specs/model-specs.json). Parameters, enums, and media roles come from here and nowhere else. |
[DREAMINA-ONLY] | A Dreamina product feature with no Higgsfield parameter behind it. Never quote these as things the user can do here. |
[EMPIRICAL — sd25-pe] | sd25-pe, a Seedance 2.5 skill file. The repo records only a Discord copy (v0.1.0, noted in the v3.33.0 changelog) and not who wrote it, so it is not labelled OFFICIAL. Its mapping-priority claim — material content outranks upload order — agrees with the one measurement here (MODE-PLAYBOOKS.md § Panel-to-timestamp mapping — board-first vs board-last, identical order adherence, on Ark). |
| Secondary labels | [OFFICIAL — Higgsfield Seedance 2.5 deck] · [DEMO — Higgsfield "AI Love Stories" tutorial] · [FIELD — AI-vs-VFX] (the build in VFX-PIPELINE.md) · [EMPIRICAL — MiniMax H3 skill corpus] · [EMPIRICAL — nutllwhy/seedance-tvc-director skill] — each named where it is used. |
Where the two disagree about what is settable, the platform snapshot wins — it is what the API actually accepts.
Pick the mode first. The same sentence means different things in different modes, and two of the four modes are not generation at all.
| The user wants | Mode | What the prompt is |
|---|---|---|
| A clip from a description, no materials | t2v | A scene brief — the core formula below |
| A clip built from images / videos / audio they supply | omni_reference | A role map plus a scene brief |
| To change something inside a video they already have | video_edit | An edit order: master + scope + preserve list |
| More footage before or after a video they already have | video_extension | A boundary contract plus new content |
Two rules that fall out of this:
omni_reference.
2.5 has no separate first/last-frame mode on this platform. The first and last frame
can go in two ways: the platform start_image / end_image roles (allowed only in
omni_reference — the catalog rejects them in t2v, video_edit and
video_extension), or ordinary references whose role sentence says they are the first
and last frame. Which of the two holds the boundary better is unmeasured; keyframes
3+ exist only in the prompt form. [OFFICIAL — Dreamina: "no need to switch to a separate first/last-frame mode"] · [OFFICIAL — platform, snapshot 2026-09-26]omni_reference with the old clip as a motion reference — not video_edit. video_edit
preserves the master's timeline and changes one scoped thing inside it.Video-to-video is not automatically
video_edit. The field VFX workflow — swap the person in this plate, keep every other pixel — runs inomni_referencewith the source attached as a video reference, because that is the lane wheredurationis settable and must be matched to the source (and where the source therefore has to be ≥ 4 s, thedurationfloor).video_editis the lane for a scoped change inside a master whose timeline must survive untouched. Full routing table + the performance-inheritance clause:VFX-PIPELINE.md§ Stage 4.[FIELD — AI-vs-VFX, 2026-08-08]
[OFFICIAL — platform, snapshot 2026-09-26] · verify against ../../specs/model-specs.json
before quoting (HARD RULE 3).
| Parameter | Values | Notes |
|---|---|---|
mode | t2v · omni_reference · video_edit · video_extension | default t2v |
duration | 4–30 s | default 5 — ignored in video_edit |
resolution | 480p · 720p · 1080p | default 720p — no 4K on 2.5 (1080p added by the 2026-09-26 snapshot; not yet field-rated) |
generate_audio | bool | default true |
bitrate_mode | standard · high | default standard |
extension_mode | backward · forward | required for video_extension, not allowed otherwise |
| aspect ratio | auto · 21:9 · 16:9 · 4:3 · 1:1 · 3:4 · 9:16 | ignored in video_edit; follows the source in video_extension |
| media roles | start_image · end_image · image_references · video_references · audio_references | start_image / end_image only in omni_reference |
The catalog also carries reference-count rules that the table cannot show
[OFFICIAL — platform, CLI rules 2026-09-26]:
t2v takes zero references — no image/video/audio references and no start/end frame.omni_reference needs at least one reference (a start or end frame counts).start_image / end_image are accepted only in omni_reference.Three consequences worth stating to the user before they spend credits:
video_edit bills by the source video's duration, and neither duration nor
aspect_ratio is settable — a 20-second master costs a 20-second render no matter how
small the edit.video_extension inherits the source's aspect ratio; only the extension's
duration is yours to set.genre parameter. 2.0's genre hint does not exist here — genre lives in the
prompt's visual-style clause instead.Preflight the same way as 2.0:
python3 scripts/seedance_lint.py --preflight --model seedance_2_5 "<prompt>"The linter reads the enums out of ../../specs/model-specs.json, so an out-of-range duration, a
4K request, or a video_extension missing its extension_mode is caught before the
render.
[OFFICIAL — Dreamina] Combine only the parts the shot needs; omit the rest rather than
padding empty slots.
<Subject> performs <primary action or event> in <scene and environment>.
The visuals feature <visual style>.
Use <shot size, camera angle, camera movement, or cuts>.
Audio includes <dialogue, ambience, sound effects, or music>.../higgsfield-seedance/SKILL.md § Prompt-Craft Laws
applies unchanged.Generation parameters are not prompt text. Resolution, duration, and aspect ratio are set on the generation page or via the API — writing them into the prose does nothing except in the modes that auto-lock them, where they are not settable at all.
The moment there is more than one material, or a material sitting next to a text
description, the prompt must state what each material contributes. [OFFICIAL — Dreamina]
@Image 1 defines <subject>'s <appearance, clothing, structure, or material>.
@Video 1 defines <motion, camera movement, or pacing>.
@Audio 1 defines <character or sound type>'s <voice, dialogue, ambience, or music>.Every material that could leak something unwanted gets an explicit exclusion in the same sentence:
@Image 2 defines the workbench and window light. Do not use the people in the image.Rules:
@Image 2. The model binds
by what it can see in the material, and a handle used as a sentence subject is the
classic way one character comes back as two people. [EMPIRICAL — sd25-pe mapping priority, re-derived 2026-08-09: material content outranks upload order] Scope:
this is the 2.5 rule. On 2.0 the house convention is the opposite — the acting paragraph
leads with the character's tag so the model binds the performance to the right person
(../higgsfield-acting/SKILL.md § Scene adaptation, ../higgsfield-seedance/SKILL.md
§ Tag naming). Handles stay in the role map on 2.5 — the [Characters] lines, a staging
legend (@A = the BLUE figure) — and out of the beat prose (../shared/house-rulings.md
P2-13). Handle spelling follows the surface: Dreamina's guide writes upload-order
handles with a space (@Image 1); the Higgsfield field build writes the upload-order form
without one (@video1) and named asset tags (@size-ref, @dragon-v3). Pick one form per
project and never mix them in one prompt.[EMPIRICAL — MiniMax H3 skill corpus, re-derived 2026-08-09; cross-model structure, unmeasured on Seedance] A role says what job a material does; it still doesn't say how much of the
material must reach the pixels. Declare one fidelity grade per material, in the same
sentence as its role:
@Image 4 defines the brocade fabric — attribute-transfer onto Mira's coat only.
Do not carry the garment's cut, the mannequin, or the studio backdrop.[OFFICIAL — Dreamina] Hard limits vs the ranges that actually stay stable:
| Type | Hard limit | Stable range |
|---|---|---|
| Images | 30, each ≤4K | 1–8 distinct subjects |
| Videos | 10, ≤30s combined | 1–5 subjects, 5–10s each |
| Audio | 10 clips, ≤30s combined | only clips directly relevant |
| Video-edit source | 1 video + reference images | source ≤20s, 1–5 reference images |
50 reference materials total. On Higgsfield the platform enforces two of these caps and
counts a start_image / end_image against both: image refs + start + end ≤ 30, all
materials + start + end ≤ 50 [OFFICIAL — platform, CLI rules 2026-09-26]. The 10-video,
10-audio and ≤30 s-combined figures are Dreamina's; no platform rule states them — treat
them as the vendor's model limits, unverified on Higgsfield. Above the stable ranges (9–12 subjects in images, 6–10 in
audio/video, 6–8 edit reference images) generation still works but stability drops and the
shot may need several attempts — budget for it, or split the scene.
More than five subjects needing multiple views → one view per image. Independent view images beat a single collage of views; the collage is the less stable form.
Spend one view on a strong expression, not four resting faces. [OFFICIAL — Higgsfield Seedance 2.5 deck, PART 2] A set of neutral views teaches the model the face at rest and
nothing else, so the first line of dialogue invents a mouth. Generate the views on a neutral
light-grey ground (shade and mechanism: ../../templates/ad-asset-prep.md § Design for win
rate) and make one of them a strong expression — anger, or a wide smile —
so the model learns the character's facial dynamics and teeth structure, not only the
resting face. The canonical four: front view · back view · facial details at neutral ·
facial dynamics and teeth under strong emotion. Close the set with the identity line
(§ Reference Roles) so all four are read as one person.
[OFFICIAL — Dreamina] The goal is not to cram every reference into one sentence. It
is to define the relationships among characters, props, scenes, actions, and audio so the
model picks the right material for the right moment.
Step 1 — name and map each subject individually. One line per subject:
<Character A> corresponds to @Image 1. Use only the appearance, hairstyle, and clothing.
<Character B> corresponds to @Image 2. Use only the appearance, hairstyle, and clothing.
<Prop A> corresponds to @Image 3. Use only the structure, material, and color.
<Scene A> references @Image 4. Use only the spatial layout, architecture, and lighting.
Do not use the people in the image.The canonical failure:
@Images 1 through 4 define four characters respectively.That sentence does not say which image is which character, and the model will guess.
Step 2 — group by type once several subjects are in play: [Characters] → [Props] →
[Scenes] → [Motion and Audio]. Add the non-interchange lock to the character group:
"Do not interchange these characters' appearances, clothing, actions, positions, or dialogue."
Step 3 — profile any recurring subject. A character crossing several scenes, or carrying several materials, gets one consolidated block:
[Subject Profile: Conservator]
Appearance and clothing: @Image 1.
Fixed prop: <Sample Case> from @Image 5.
Locations: <Conservation Lab> and <Gallery>.
Motion references: the case-opening motion from @Video 1.
Do not use: other characters' clothing. Do not give this character other equipment.Step 4 — select references by scene. Per scene, list only the subset actually used, then the event and its end state:
Scene 1 | Inspection in the Conservation Lab
Use: <Conservator>, <Sample Case>, <Conservation Lab>, and the case-opening motion from @Video 1.
Event: <Conservator> opens <Sample Case> at the workbench and inspects the sample inside.
End state: <Conservator> remains on the inner side of the workbench. <Sample Case> stays
beside the conservator's right hand.Step 5 — check ownership. Props belong to exactly one character ("belongs only to
<Conservator>"); character count, clothing, and spatial direction stay constant across scenes.
[OFFICIAL — Dreamina] 2.5 generates up to 30 seconds natively. Anything with several
events gets staged — one flat paragraph is where dropped beats come from.
Each stage carries exactly one primary state change and closes on an explicit, directly visible end state. Each new stage restates what carries over.
[Generation Goal]
Generate a <video type>. The central subject is <subject>, and the primary event is <story summary>.
[Stage 1]
Initial state: <initial state of characters, props, and scene>.
Primary event: <one primary action or event>.
End state: <character positions, prop ownership, or visible scene state>.
[Stage 2]
Continue from the previous stage: <state that must remain unchanged>.
Primary event: <one primary action or event>.
End state: <observable state>.
[Stage 3]
Primary event: <closing event>.
End state: <final visible state>.
[Maintain Consistency]
Keep <character identity, number of characters, clothing, prop ownership, spatial direction,
and audio relationships> consistent.Staging solves too many events in one paragraph. It does not solve two incompatible jobs in one generation, and that is a separate cut worth making [DEMO — Higgsfield "AI Love Stories" tutorial, 2026-08].
The reported case: an arena scene containing a fight (a giant throw, a sword snatch, a takedown) and, in the same beat, the acting around it (a hidden worry, a flirtatious exit, hope draining from a face). Run as one prompt it held — badly, in both directions at once: "the fight gets softer, the faces get flatter." The model spends its attention budget once. Asked to nail physics and micro-performance in one generation, it half-does each.
Split into two prompts, one job each, stitched in the edit:
| Cut it here | Because |
|---|---|
| physics ↔ performance | mass, contact and follow-through vs. eyes, breath and micro-expression. Different attention, different optics, usually different shot sizes |
| action ↔ dialogue | the same split wearing other clothes |
| the beat that needs room | the second reported case: a 30s carnival scene held as one prompt, and was still split into 3×15s because the first-touch beat needed room — "these beats felt completely rushed". Length was not the constraint; pacing was |
How to tell which cut you need. Length-driven splits are decided by counting events. This one is decided by asking: what is this shot's dominant job? If a prompt has two honest answers, it has two shots in it. That is the same question the Feasibility Veto asks about a single frame, applied to a whole generation.
Note the direction of the second case: it fit, and was split anyway. "It generated" is not the bar — a scene that renders every beat but rushes the one that matters has failed at the thing you were making it for.
Practical consequence, stated plainly by the same production: a perfect 30s render does not exist. Generate raw footage per job, then assemble. Several of the finished scenes in that film take the background from one take and the foreground action from another.
Stages are the default. Reach for one-second precision only when a specific handoff, entrance/exit, transition, or beat must land on a moment.
| Pattern | Use for | Example |
|---|---|---|
| Time range | Allocating pacing to a segment | 0-3 seconds… 3-7 seconds… 7-12 seconds… |
| Exact time point | One key event | At 5 seconds, the camera whip-pans rapidly to the left and completes the transition. |
| Relative timing | A delay between two events | Three seconds after the character presses the button, the room lights gradually turn off. |
Relationship to 2.0's beat arithmetic.
../higgsfield-seedance/SKILL.md§ Output Format requires timed beats to sum to the declared duration. That still holds — but sum to 4–30s here, and remember that on 2.5 the sum is a budget the model approximates, not a cut list it honours to the frame.
[OFFICIAL — Dreamina] Prompts can be written entirely in natural language. Use the
brackets when music, SFX, dialogue, and subtitles must be told apart explicitly:
| Content | Syntax | Example |
|---|---|---|
| Music | () | (Soft, rhythmic piano music plays in the background) |
| Sound effects | <> | <A bell rings in the distance> |
| Dialogue | {} | {Hello, welcome back.} |
| Subtitles | 【】 | 【Chapter One: Departure】 |
Dialogue language reinforcement. For non-Chinese dialogue — or when English text comes back spoken in Chinese, or a specific regional variety is wanted — state it before the line:
Dialogue language + regional variety or accent + delivery style + speaker + {dialogue}Dialogue language: authentic Los Angeles English. The man says in natural Los Angeles
vernacular: {No way, you actually made it.}Adapted: as first recorded here, this example inside the [OFFICIAL — Dreamina] section
named the speaker by an age word; rewritten age-blind per
../higgsfield-seedance/ENGINE-RULES.md rule 1. The structure is Dreamina's.
Two house rules carry over from ../higgsfield-audio/SKILL.md and the film pipeline in
../higgsfield-seedance/HELL-GRIND.md:
they exchange a look that says "you too?" is a line the script
never wrote, and it comes back spoken. [EMPIRICAL — nutllwhy/seedance-tvc-director skill (MIT), re-derived 2026-08-09; the failing take is timecoded in that evaluation] Anything readable is a
voicing request — quoted subtext, a remembered line, a slogan, a sign read aloud. Write
the visible behavior instead (jaw sets, eyes hold), and note that adding "no dialogue"
does not undo it: the readable text is still there being asked for.[OFFICIAL — Dreamina]. Still say it — and no 【】 block — rather
than trusting the improvement. One part is settled: lead with the positive diegetic
list (the sources and room tone the audio is). One is a default: never put the
suppression inside the () bracket — () is the music channel, so (no music) there
is most likely read as a music cue. That is a [HOUSE] inference, not a measurement; it
stands as the default because writing the suppression as plain audio text after the list
costs nothing (../shared/house-rulings.md P2-7). Which token to write —
NO BGM (one third-party skill: a production term reads as a hard spec,
../higgsfield-audio/SKILL.md § Suppressing music [EMPIRICAL]) or No music. (the
form 12 of 13 harvested projects shipped, ../../templates/seedance/global-style-prefix.md
[FIELD]) — is OPEN, unmeasured here (../shared/house-rulings.md P2-7).[OFFICIAL — Dreamina] On 2.5 these are not a mode — they are omni_reference work.
Since the 2026-09-26 snapshot the platform also exposes start_image / end_image roles
(omni_reference only), so the first and last frame have two routes:
start_image / end_image. Keep a short role
sentence in the prompt anyway (what the frame fixes, what may change) so the prose and the
attachment agree. [OFFICIAL — platform, snapshot 2026-09-26]image_references and name
their roles in prose (template below). This is the form ByteDance's guide documents, and
the only form for keyframes 3+.Which route holds the boundary better is unmeasured — no O-Side generation compares them. Don't do both for the same image (one image, one role).
@Image 1 is the first frame. It defines the opening composition, subject position, pose,
prop state, scene, and camera direction.
@Image 2 is the last frame. It defines the ending composition, subject position, pose,
prop state, scene, and camera direction.
@Image 3 defines <Subject A>'s <appearance, clothing, structure, or material>. Do not change
the first-frame composition defined by @Image 1 or the last-frame composition defined by @Image 2.
<Describe one continuous action or event>.
The video begins naturally from the first frame defined by @Image 1 and reaches the last
frame defined by @Image 2 after the continuous action.
Between the first and last frames, maintain continuity in <character identity, prop structure
and ownership, scene layout, and camera direction>.Three failure sources, all avoidable:
@Images 1 and 2 are the first and last frames is the
documented wrong form. One role sentence per image.start_image role.)Multi-keyframe sequences (3+ ordered stage images) open with Use @Image 1 through @Image N as keyframes in this order, then describe the key state each image represents.
Independent keyframe images align far more reliably than several frames combined into one
grid. Keyframes control stage order and key states — they do not reproduce every
intermediate frame.
Storyboard grids and blockout references (coarse vs fine) are the next rung up:
MODE-PLAYBOOKS.md § Storyboard grids and § Blockout references.
The long templates live in MODE-PLAYBOOKS.md in this directory. What you need to know
before opening it:
Material Roles → Image Order → Motion Amount → Editing Style → Visual Treatment → Audio. "Turn these into a video" is never enough.Before Video → After Video → Trigger Action → Camera Movement → Visual Transformation → Arrival State → Audio.[OFFICIAL — Dreamina]
Emotion. Abstract words ("tense", "warm", "oppressive") set a direction and leave the rest to interpretation. Pair them with directly visible or audible cues — eye movement, brow tension, mouth movement, breathing, gaze direction, hand movement. Two to four cues is enough for one transition; listing every facial detail is counterproductive.
The overall emotion shifts from <starting emotion> to <ending emotion>.
After <triggering event>, <subject> first shows <immediate observable reaction>.
Then, <eyes, brows, mouth, breathing, gaze, or hand movement> gradually <changes>.
Finally, <subject> expresses <target emotion> through <restrained or explicit outward behavior>.Use event-triggered multi-stage form only when the emotion genuinely changes several times.
For muscle-level control beyond this, ../higgsfield-facs/SKILL.md (AU codes); for the
behavior-under-pressure layer that makes the cues mean something,
../higgsfield-acting/SKILL.md.
Camera terms. Basic language works directly — shot size (extreme wide / wide / medium / close-up / extreme close-up), movement (push in, pull out, pan, lateral move, follow, orbit, dive, dolly out, tilt up, handheld shake), position (low angle, overhead, first-person).
Popular techniques (one-take, dolly zoom, aerial, FPV, bullet time, handheld, bounce speed ramp) also work directly — but with several subjects in frame, still say which subject the camera follows or orbits, where the move starts, and where it ends.
For a niche or ambiguous term, keep the term and translate it into an observable result:
Cinematography term + target subject + visual change + foreground/background relationship + direction or speedRack focus: shift focus smoothly from the leaves in the foreground to the person in the
background. The leaves gradually blur while the person's face changes from soft to sharp.For a precise transition moment, add the trigger time, the occluding object, the direction, and what continues afterwards. Aperture/focal-length/shutter numbers are allowed but the intended visible result is clearer than a raw value alone.
FOV degrees still beat millimetres. The discrete-anchor FOV bank in
../higgsfield-seedance/SKILL.md§ FOV anchors is house doctrine across the Seedance family and applies here unchanged.
[OFFICIAL — Dreamina] The vendor's answer to "my characters look AI, or look like twins"
is a seven-slot character block. It works for stylized characters too.
[Role] [Skin color / skin texture] [Facial details] [Eyes / soul]
[Hairstyle / hair color] [Clothing / clothing texture] [Body type / mood / temperament]
[Other requirements, if any]Slot notes:
../higgsfield-acting/SKILL.md § Eye life.House override on slot 1. The source guide labels the first slot
[Age/Race]. Do not write age. Engine rule 1 in../higgsfield-seedance/ENGINE-RULES.mdis age-blind characters, and Higgsfield's own feature-film brief gives the reason: the content filter tightens sharply the moment it reads a minor. Write role, build, clothing, and action instead — "a lean courier in a soaked parka", not "a 22-year-old". Ethnicity stays a normal descriptive slot; age does not.
| The job needs | Model |
|---|---|
| 4K output | 2.0 (mode=std) — 2.5 stops at 1080p |
A genre hint parameter, or mode=fast | 2.0 |
| 1080p output | either — 2.0 needs mode=std; 2.5's 1080p is not yet field-rated |
| Platform start / end frame | either — 2.0 in any reference setup; 2.5 only in omni_reference |
| A clip longer than 15 seconds in one generation | 2.5 (up to 30s) |
| Editing a video that already exists | 2.5 (video_edit) |
| Extending a clip forward or backward | 2.5 (video_extension) |
| More than 9 reference images, or >3 reference videos/audio clips | 2.5 (30 / 10 / 10 vs 2.0's 9 / 3 / 3) |
| Cheap 480p prompt validation | either — both cap the draft lane at 480p |
The honest default: draft and structure on 2.5 when the job is long, reference-heavy, or
edit-shaped; finish on 2.0 when the deliverable needs 4K. They are not
interchangeable takes — a 2.5 draft validates the prompt, not the 2.0 render, for the same
reason ../higgsfield-seedance/SKILL.md § Drafts Validate the Prompt gives: there is no
seed to pin.
The engine rules are shared. ../higgsfield-seedance/ENGINE-RULES.md applies in full —
age-blind characters, exit-frame = implicit cut, off-screen = nonexistent, avoid reflection
shots, ≤3 tracked characters, double-contrast cuts, micro-expressions as physics. So do the
positive-phrasing law (stated for 2.0 as an empirical law — Seedance parses negative-list
syntax as scene description; for 2.5 it is carried over by house assumption, unmeasured),
the homograph trap, and the block scaffold for production-scale briefs.
[OFFICIAL — Dreamina]
[DREAMINA-ONLY] These exist in ByteDance's own Dreamina/Jimeng product and appear in the
guides, but there is no Higgsfield parameter behind them on the 2026-09-26 snapshot. Do
not offer them here.
| Dreamina feature | Status on Higgsfield | Closest thing that does work |
|---|---|---|
| Ultra Long Video — 30–180s in one generation | Not exposed; duration caps at 30 | Stage a 30s generation and extend it once, to the 60 s single-chain ceiling (§ Extension chain math below); past that, re-anchor from the original references and assemble in post |
| Nested extension to 60s via repeated UI operations | The model rule (source ≤30s → extend up to 30s) holds; the one-click nesting UI does not exist | Chain video_extension calls, re-checking the boundary each time |
| Edit with marks / Advanced Edit — box, arrow, brush, anchor annotations on a frame | Not exposed; there is no annotation channel | video_edit with a written scope: object + change + effective time range |
| Clay Renderer plugin — white-model rendering workflow | Not exposed as a plugin | Coarse/fine blockout prompting via omni_reference (MODE-PLAYBOOKS.md § Blockout references) |
| Native 180s / multi-minute deliverables | — | Generate in 30s pieces and assemble in post (../higgsfield-pipeline/SKILL.md) |
Extension chain math. The model-side rule is: a source within 30 seconds can be
extended by 4–30 seconds in one operation, so a 30s source plus a 30s extension is the
60-second ceiling for a single chain. Beyond that, re-anchor from the original references
rather than extending an extension — the same degradation curve as 2.0's chain cap in
../higgsfield-seedance/SKILL.md § Extension Prompting.
[OFFICIAL — Dreamina], plus the house preflight. Only the rows for techniques actually used:
omni_reference only; one route per image (platform role or in-prompt role), matching aspect ratios, anchors not mergedseedance_lint.py --preflight --model seedance_2_5 run and clean../higgsfield-seedance/SKILL.md — Seedance 2.0 director: the filter model, block scaffold,
FOV anchors, prompt-craft laws, engine rules. Everything model-agnostic lives there.../higgsfield-seedance/ENGINE-RULES.md — the shared hard rendering constraints../higgsfield-seedance/HELL-GRIND.md — Higgsfield's open-sourced feature-film pipeline
(assets, GEO spatial layout, dialogue construction, iteration discipline)../higgsfield-acting/SKILL.md — performance: objective, obstacle, tactics, beats, eye life../higgsfield-facs/SKILL.md — facial control by Action Unit code../higgsfield-seedance-vfx/SKILL.md — video-to-video footage transforms on 2.0../higgsfield-models/SKILL.md — model choice against the specs layer../higgsfield-pipeline/SKILL.md — assembling 30-second pieces into a longer deliverableMODE-PLAYBOOKS.md — the editing / extension / one-click / transition / blockout templatesVFX-PIPELINE.md — the AI-VFX production pipeline: asset-class model routing, the size-ref
frame, location batching, the omni_reference v2v lane, the four-batch rule, the slop catalog© OSideMedia, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 2 other files in skills/higgsfield-seedance-2-5 of OSideMedia/higgsfield-ai-prompt-skill.
Open the folder on GitHubat commit 7075497
Higgsfield Seedance 2 5 next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Higgsfield Seedance 2 5 this skillOSideMedia/higgsfield-ai-prompt-skill | 713 | — | ~11k | Automated safety check: Pass | MIT | |
| Scroll Promo Site Builderkangarooking/kangarooking-skills | 662 | — | ~2.6k | Automated safety check: Pass | MIT | |
| AI Marketing VideosNeverSight/learn-skills.dev | 217 | 3 repos | ~2.1k | Automated safety check: Pass | None | |
| Seedance ContinuationEmily2040/seedance-2.0 | 7.6k | 1 repos | ~2k | Automated safety check: Pass | MIT | |
| Seedance Viral Hookrediumvex/ai-video-generator-claude | 409 | — | ~4.6k | Automated safety check: Pass | MIT | |
| Seedance Course Promorediumvex/ai-video-generator-claude | 409 | — | ~5.5k | Automated safety check: Pass | MIT |
kangarooking/kangarooking-skills
Create a scroll-controlled cinematic product website with rich motion (动效网站) from product materials, reference pages or videos, and brand assets.
NeverSight/learn-skills.dev
Create AI marketing videos for ads, promos, product launches, and brand content.
Emily2040/seedance-2.0
Writes continuation prompts for Seedance 2.0 video from accepted footage: next shots, bridge clips, tail repair and re-anchoring after drift, gated on real clip records.
rediumvex/ai-video-generator-claude
Generate scroll-stopping viral hook video prompts for Seedance 2.0 on Higgsfield.
rediumvex/ai-video-generator-claude
Generate online course and coaching program promotional video prompts for Seedance 2.0 on Higgsfield.
pexoai/pexo-skills
AI video generation skill with auto model selection across Seedance 2, Kling 3.0, HappyHorse, and 10+ models.
OSideMedia/higgsfield-ai-prompt-skill
A skill your agent uses whenever the user asks anything about Higgsfield AI — writing or refining video/image prompts, choosing a model (Kling, Veo, Wan, Seedance, Minimax Hailuo, DoP, Soul, Nano…
OSideMedia/higgsfield-ai-prompt-skill
A skill your agent uses when the user asks about Higgsfield Assist (the built-in GPT-5 copilot), how to use the platform's native AI assistant, credit optimization strategies, plan selection, how to…
OSideMedia/higgsfield-ai-prompt-skill
A skill your agent uses when the user wants to generate a cinematic still image on Higgsfield, asks about shot framing, camera angle, or composition for image prompts, needs a specific shot type…
OSideMedia/higgsfield-ai-prompt-skill
A skill your agent uses when the user asks about Mixed Media, wants to apply artistic preset styles to an image (Noir, Sketch, Paper, Canvas, Particles, Neon, etc.), combine multiple artistic…
OSideMedia/higgsfield-ai-prompt-skill
A skill your agent uses when the user asks about Moodboard, building a moodboard from reference images, curated moodboard presets, Soul Hex color transfer, applying a visual style direction to…
OSideMedia/higgsfield-ai-prompt-skill
A skill your agent uses when the user wants to apply a named Higgsfield motion preset, asks about VFX presets, transformation effects, elemental effects, or transition presets.
Works with
Categories
Seedance 2.5 prompt director — the omni-reference dialect. An agent skill from OSideMedia/higgsfield-ai-prompt-skill. Higgsfield Seedance 2 5 is an agent skill from OSideMedia/higgsfield-ai-prompt-skill.5 prompt director — the omni-reference dialect.
Higgsfield Seedance 2 5 fits situations like: the user asks for a Seedance 2.5 prompt; mentions Seedance 2.5 / Dreamina / Jimeng; wants a clip longer than 15s on Seedance; EXTEND an existing video rather than generate a new one.
Run `npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield-seedance-2-5 -a claude-code`. Or copy the skill folder (skills/higgsfield-seedance-2-5 in OSideMedia/higgsfield-ai-prompt-skill) into .claude/skills/higgsfield-seedance-2-5 in your project. Claude Code loads it when a task matches its description.
Run `npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield-seedance-2-5 -a codex`. Or copy the skill folder (skills/higgsfield-seedance-2-5 in OSideMedia/higgsfield-ai-prompt-skill) into .agents/skills/higgsfield-seedance-2-5 in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield-seedance-2-5 -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/higgsfield-seedance-2-5, .gemini/skills/higgsfield-seedance-2-5, .github/skills/higgsfield-seedance-2-5 and .opencode/skills/higgsfield-seedance-2-5 in your project.
Going by SKILL.md and its folder, Higgsfield Seedance 2 5 needs the command-line tools its instructions call (python3).
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Higgsfield Seedance 2 5 is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 11k tokens (SKILL.md is roughly 46k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Higgsfield Seedance 2 5: Scroll Promo Site Builder (kangarooking/kangarooking-skills, 662 stars), AI Marketing Videos (NeverSight/learn-skills.dev, 217 stars), Seedance Continuation (Emily2040/seedance-2.0, 7.6k stars) and Seedance Viral Hook (rediumvex/ai-video-generator-claude, 409 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
OSideMedia (a GitHub user) maintains it in OSideMedia/higgsfield-ai-prompt-skill, which has 713 GitHub stars. The repository holds 33 skills in this directory. The repository was last updated on September 27, 2026.
Source: OSideMedia/higgsfield-ai-prompt-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.