Storyboard Generator

Estimated credits: ~24 per run.

Inputs

premise

scenes

style

Steps

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.