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Get Started Free →samuraigpt/muapi-ai-fight-scene
Generate a high-cut-density action / fight scene by first composing a 16-cell storyboard image, then driving Seedance 2.0 image-to-video off that storyboard. Stacks GPT-Image-2 (character sheet + storyboard), Nano-Banana-2 (environment concept), and Seedance 2.0 i2v.
Passed 20 of 22 test cases with the skill, and 5 of 22 without it.
and 27 more in the full report
15 fixed5 passed either way2 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 15 test cases the skill fixed. Same model, same prompt, with and without the skill.
When setting up Phase B to generate the stage setting visual plate for a wet back-alley brawl, which model is specified and what constraint must be enforced in the prompt content?
| Checked | Without skill | With skill |
|---|---|---|
| Selects nano-banana-2 as the image generator model. | Missed | Passed |
| Requires specifying no characters in frame within the prompt. | Passed | Passed |
The instructions your model reads when the skill loads.
Generate a high-cut-density action / fight scene by first composing a 16-cell storyboard image, then driving Seedance 2.0 image-to-video off that storyboard.
The core idea: action tension comes from cut density, not single-shot quality. Forcing the video model to follow a pre-drawn 4×4 storyboard grid gives you 16 distinct shots in a 15-second clip — landing punches, reverse angles, ECUs, whip-pans — that no t2v prompt could choreograph on its own.
| Name | Type | Required | Default | Description |
|---|---|---|---|---|
character_description | text | yes | — | Full physical description of the fighter(s). Asymmetric details (eye colour, scar side, holster on left hip) help the model preserve identity across panels. |
environment_description | text | yes | — | The scene setting — e.g. "cyberpunk wet back-alley, neon kanji signage, Stray-game aesthetic, rain on chrome." |
action_script | text | yes | — | The action beat — prose or numbered beats. E.g. "Hero is cornered → blocks first punch → counter-elbow → throw opponent into trash cans → finisher." |
style_direction | text | no | cinematic action film, anamorphic lens, high contrast, motion blur on hits | Aesthetic / look tags applied to every frame. |
duration | int | no | 15 | Final video length in seconds. The storyboard's 16 cells map roughly 1 shot per second at default. |
aspect_ratio | text | no | 16:9 | Output aspect — 16:9 cinematic, 9:16 vertical, 1:1 square. |
Generate a clean turnaround-style character sheet using muapi image generate (model=gpt-image-2-text-to-image):
Character reference sheet of {{character_description}}. Three views — front, 3/4, profile — on a neutral grey backdrop. Studio lighting, full body, no text overlays, photoreal. Asymmetric identifying details preserved on the correct side. {{style_direction}}.3:2Present the character sheet and confirm identity details look right before proceeding. This image becomes reference #1 for later phases.
Use muapi image generate (model=nano-banana-2) to design the scene/world:
Wide establishing shot of {{environment_description}}. No characters in frame — environment only. Strong perspective lines, depth, atmospheric haze. {{style_direction}}. Production-design concept art.{{aspect_ratio}}Nano-Banana-2 is chosen here for its reasoning-driven composition — it's better than text-to-image-only models at producing locations with believable spatial logic (chokepoints, cover, sightlines) that an action scene can use. Present for approval. This becomes reference #2.
test cases passed, vs 5 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.