opencode Skill

muapi-storyboard

Generate N keyframes for a short story or scene sequence (image only, no video).

LLM Mart · 0 points · 12 0 0

Virus-scanned Reviewed automatically before listing.

Full trust report

Download samuraigpt-generative-media-skills-library_visual_storyboard-74df8cb.zip · 1 KB

samuraigpt/generative-media-skills 4295 492 forks MIT Updated 17d ago

Part of samuraigpt/generative-media-skills — 72 skills

Install

skills CLI npx skills add https://github.com/SamurAIGPT/Generative-Media-Skills/tree/main/library/visual/storyboard

Claude Code

claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install samuraigpt-generative-media-skills@llmmart

Git git clone https://github.com/SamurAIGPT/Generative-Media-Skills.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole samuraigpt/generative-media-skills collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

Storyboard Generator

Generate N keyframes for a short story or scene sequence (image only, no video).

Inputs

Name	Type	Required	Default	Description
`premise`	text	yes	—	One-line story premise (e.g. "lonely robot finds a tiny mechanical bird friend").
`scenes`	int	no	6	Number of keyframes to produce.
`style`	text	no	cinematic, photoreal, soft lighting, 16:9	Visual style tags applied to every keyframe.

Steps

Use the plan to dispatch all N keyframes in a single parallel layer.

Decompose premise into {{scenes}} story beats with a clear arc: setup → inciting moment → escalation → climax → resolution.
- Each beat gets a one-paragraph visual description.
- Maintain character / object continuity across beats (same character appearance, same world).
For each beat, create a muapi image generate node (model=nano-banana-2, aspect_ratio=16:9):
- Prompt = "<beat description>. {{style}}".
- Tier: balanced (these are reference keyframes, not finals).
- Aspect ratio: 16:9.
Run the plan in parallel (no depends_on between keyframes).
Return the asset ids in beat order with a one-line caption per scene.

Notes

Don't animate, upscale, or add audio — this skill is keyframes only. If the user wants video, suggest the music-video skill afterward.
For consistency, repeat character description verbatim in every prompt ("a small rusty humanoid robot with…") rather than relying on the model to remember.

Trigger Keywords

storyboard, keyframes, scene sequence, story panels

Notes for the Executing Agent

This recipe is LLM-orchestrated: read each phase, gather any missing inputs from the user, then call muapi CLI commands. Use muapi auth configure first if MUAPI_API_KEY is unset.
For model IDs without a CLI alias yet, fall back to the raw endpoint via curl -X POST https://api.muapi.ai/api/v1/<endpoint> -H "x-api-key: $MUAPI_API_KEY" -H 'content-type: application/json' -d '{...}' and poll with muapi predict wait <request_id>.
Substitute {{input_name}} placeholders with the user's actual inputs before issuing each call.

Files (generative-media-skills)

SKILL.md 2.4 KB

---
slug: muapi-storyboard
name: muapi-storyboard
version: "1.0.0"
description: Generate N keyframes for a short story or scene sequence (image only, no video).
acceptLicenseTerms: true
---


# Storyboard Generator

**Generate N keyframes for a short story or scene sequence (image only, no video).**

## Inputs

| Name | Type | Required | Default | Description |
|:---|:---|:---|:---|:---|
| `premise` | text | yes | — | One-line story premise (e.g. "lonely robot finds a tiny mechanical bird friend"). |
| `scenes` | int | no | 6 | Number of keyframes to produce. |
| `style` | text | no | cinematic, photoreal, soft lighting, 16:9 | Visual style tags applied to every keyframe. |


## Steps

Use the plan to dispatch all N keyframes in a single parallel layer.

1. Decompose `premise` into `{{scenes}}` story beats with a clear arc:
   setup → inciting moment → escalation → climax → resolution.
   - Each beat gets a one-paragraph visual description.
   - Maintain character / object continuity across beats (same character
     appearance, same world).
2. For each beat, create a `muapi image generate` node (model=nano-banana-2, aspect_ratio=16:9):
   - Prompt = `"<beat description>. {{style}}"`.
   - Tier: balanced (these are reference keyframes, not finals).
   - Aspect ratio: 16:9.
3. Run the plan in parallel (no `depends_on` between keyframes).
4. Return the asset ids in beat order with a one-line caption per scene.

## Notes
- Don't animate, upscale, or add audio — this skill is keyframes only.
  If the user wants video, suggest the `music-video` skill afterward.
- For consistency, repeat character description verbatim in every prompt
  ("a small rusty humanoid robot with…") rather than relying on the model
  to remember.

## Trigger Keywords

`storyboard`, `keyframes`, `scene sequence`, `story panels`


---

## Notes for the Executing Agent

- This recipe is LLM-orchestrated: read each phase, gather any missing inputs from the user, then call `muapi` CLI commands. Use `muapi auth configure` first if `MUAPI_API_KEY` is unset.
- For model IDs without a CLI alias yet, fall back to the raw endpoint via `curl -X POST https://api.muapi.ai/api/v1/<endpoint> -H "x-api-key: $MUAPI_API_KEY" -H 'content-type: application/json' -d '{...}'` and poll with `muapi predict wait <request_id>`.
- Substitute `{{input_name}}` placeholders with the user's actual inputs before issuing each call.