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.
Skill by SamurAIGPT
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
Use cases: spreadsheets
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Permissions
What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.
- Tools
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/muapi-ai-fight-scene
What's inside
- Skill name
muapi-ai-fight-scene- Description
- 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.
- License
- MIT
- Instructions
- 126 lines in SKILL.md · view on GitHub
Before installing
- Instructions call the network
Agent Skills spec issues
- name: "muapi-ai-fight-scene" does not match folder "ai-fight-scene"
Files (1)
- SKILL.md
SKILL.md (first lines)
# AI Fight Scene Generator
**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.
## Inputs
| 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. |
## Steps
### Phase A — Character Sheet
Generate a clean turnaround-style character sheet using `muapi image generate` (model=`gpt-image-2-text-to-image`):
- Prompt: `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}}.`
- Aspect ratio: `3:2`
Present the character sheet and confirm identity details look right before proceeding. **This image becomes reference #1 for later phases.**
### Phase B — Environment Concept
Use `muapi image generate` (model=`nano-banana-2`) to design the scene/world:
- Prompt: `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: `{{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.**
### Phase C — 16-Cell Storyboard
Compose the action onto a single 4×4 storyboard image using `muapi image edit` (model=`gpt-image-2-image-to-image`):
- Reference Images: the character sheet from Phase A **and** the environment plate from Phase B.
- Prompt:
```
Compose a 4×4 storyboard grid (16 numbered cells) for the following action sequence:
{{action_script}}
CHARACTER (use reference image 1 identity throughout, asymmetric details preserved):
{{character_description}}
LOCATION (use reference image 2 spatial layout):
{{environment_description}}
Each cell labels: SHOT # (1–16) · SIZE (WIDE / MS / CU / ECU) · CAMERA-MOVE arrow (push, pull, whip, dolly, crash-zoom, handheld) · 1-word RHYTHM note (BEAT / IMPACT / RECOVERY / RESET).
Vary shot size aggressively — never two WIDEs in a row. Land every IMPACT on a CU or ECU.
Hand-drawn comic-book ink-and-wash style, monochrome with selective red accents on hits.
Numbered cells, clear gutters between panels.
Aesthetic: {{style_direction}}.
```
- Aspect ratio: `1:1` (square works best for a 4×4 grid)
Present the storyboard to the user. Confirm:
- The 16 shots read clearly
- Identity stays consistent cell-to-cell
- Cut density / shot-size variation looks aggressive enough
If a panel reads poorly, regenerate just the storyboard with that cell's note bolded ("CELL 7 must be an ECU on the right fist").
### Phase D — Storyboard → Video (Seedance 2.0)
Hand the storyboard to `muapi video from-image` (model=`seedance-v2.0-i2v`):
- Reference Image: the 16-cell storyboard from Phase C.
- Prompt:
```
Generate a {{duration}}-second action sequence that strictly follows the 16-cell storyboard reference image, cell-by-cell, top-left to bottom-right.
- Honour each cell's labelled SHOT SIZE and CAMERA-MOVE — match cuts to the storyboard's rhythm notes.
- Strong cinematic feel and shot language. Exaggerated dynamics. Hits land hard with motion blur and impact frames.
- Camera language: anamorphic, handheld where the storyboard calls for it, locked-off where it doesn't.
- Native audio: impact sfx on every IMPACT cell, footsteps, fabric/Foley, restrained low score under the action.
Action being rendered: {{action_script}}.
Aesthetic: {{style_direction}}.
```
- Duration: `{{duration}}` (default 15)
- Aspect ratio: `{{aspect_ratio}}`
After generation, present the final video. If the cut density feels too low or shots don't match the storyboard, regenerate Phase D first (cheaper than rebuilding the storyboard) with the prompt emphasising "strict cell-by-cell adherence" more aggressively.
## Notes
- **Why the storyboard image and not a text storyboard?** Seedance 2.0 i2v anchors its motion plan to the visual reference. A grid of 16 drawn cells gives it 16 visual targets to hit — text descriptions of shots get averaged into mush.
- **Asymmetric character details matter.** Without something like "scar over the right eyebrow" or "leather glove on the left hand only", identity drift between cells is the #1 failure mode.
- **Use `seedance-2.0-i2v-480p` to draft.** Cheaper preview pass before committing to the full-res `seedance-v2.0-i2v` run.
- **For longer fights**, chain two runs: first run uses storyboard A (cells 1–16, beats 1–15s); second run uses storyboard B (cells 17–32, beats 15–30s) with the last cell of A as a continuity anchor in B's first cell.
- **Language**: Both English and Chinese prompts work in all four models, so the storyboard cell labels can be in either language.
## Trigger Keywords
`fight scene`, `action sequence`, `storyboard to video`, `cut density`, `cinematic action`, `combat choreography`, `seedance 2 storyboard`
## Pipeline at a Glance
```
character_description ──► [GPT-Image-2 t2i] ─► character sheet ──┐
│
environment_description ─► [Nano-Banana-2 t2i] ─► environment plate ┼─► [GPT-Image-2 i2i] ─► 16-cell storyboard ─► [Seedance 2.0 i2v] ─► 15s action video
│
action_script + style_direction ───────────────────────────────────►┘
```
---
## Notes for the Executing AgentFrom SamurAIGPT/muapi-skills, MIT.
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Signals
- Stars
- 7
- Forks
- 2
- Open issues
- 0
- Last commit (this folder)
- Oct 1, 2026 (1 month ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/SamurAIGPT/muapi-skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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muapi-ai-fight-scene skill. Agent Mart. https://agentmart.dev/skills/samuraigpt-muapi-ai-fight-scene (last updated 2026-10-24)