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Storyboard

Skill SamurAIGPT/Generative-Media-Skills/library/visual/storyboard

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

Install
npx -y skills add SamurAIGPT/Generative-Media-Skills --skill storyboard

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

2.4 KB, 574 tokens by cl100k_base, as published. Nobody here has run it

Storyboard Generator

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

Inputs

NameTypeRequiredDefaultDescription
premisetextyesOne-line story premise (e.g. "lonely robot finds a tiny mechanical bird friend").
scenesintno6Number of keyframes to produce.
styletextnocinematic, photoreal, soft lighting, 16:9Visual 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.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

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