Mmcp.market

muapi-storyboard skill

by SamurAIGPT·SamurAIGPT/Generative-Media-Skills·4.3k stars·MIT

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

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Install the muapi-storyboard skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description. 

git clone --depth 1 https://github.com/SamurAIGPT/Generative-Media-Skills.git /tmp/Generative-Media-Skills
mkdir -p ~/.claude/skills
cp -r /tmp/Generative-Media-Skills/library/visual/storyboard ~/.claude/skills/muapi-storyboard
available in every project

In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it on GitHub

Storyboard Generator

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

Inputs

Steps

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

setup → inciting moment → escalation → climax → resolution.

  1. Decompose premise into {{scenes}} story beats with a clear arc:

appearance, same world).

  • Each beat gets a one-paragraph visual description.
  • Maintain character / object continuity across beats (same character
  1. For each beat, create a muapi image generate node (model=nano-banana-2, aspect_ratio=16:9):
  • Prompt = ". {{style}}".
  • Tier: balanced (these are reference keyframes, not finals).
  • Aspect ratio: 16:9.
  1. Run the plan in parallel (no depends_on between keyframes).
  2. Return the asset ids in beat order with a one-line caption per scene.

Notes

If the user wants video, suggest the music-video skill afterward.

  • Don't animate, upscale, or add audio — this skill is keyframes only.

("a small rusty humanoid robot with…") rather than relying on the model to remember.

  • For consistency, repeat character description verbatim in every prompt

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 MUAPIAPIKEY 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/ -H "x-api-key: $MUAPIAPIKEY" -H 'content-type: application/json' -d '{...}' and poll with muapi predict wait .
  • Substitute {{input_name}} placeholders with the user's actual inputs before issuing each call.

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