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huikku

pixmax-mcp

by huikku

Generate a storyboard panel

generate_storyboard

Generate single storyboard panels using AI models like GPT Image or Banana. Supports consistency through reference images with role, strength, and note guidance.

Instructions

Generate an image via the GENERATE_STORYBOARD node type (GPT Image 2, Nano Banana 2, Nano Banana Pro). Identical to generate_image — same pricing, same single-image output — just classified under a different node type. No multi-panel behavior; use generate_image unless something downstream specifically requires the GENERATE_STORYBOARD classification. Pass reference_images for consistency.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
waitNoDefault true. false = return a task id immediately (poll with get_task)
countNoNumber of panels (billed linearly)
modelNoStoryboard-capable model (default BANANA_PRO). Also GPT_IMAGE_2, BANANA_2.
styleNoVisual-language suffix for a consistent board set
promptYesThe panel to generate
save_toNoDirectory to save the result(s) — Pixmax URLs expire
resolutionNoe.g. 1K, 2K, 4K — free on most models
aspect_ratioNoe.g. 16:9, 1:1, 9:16
reference_imagesNoReferences with optional role/strength/note guidance
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so the description carries the full burden. It discloses pricing, single-image output, reference_images for consistency, and the node type classification. However, the claim of 'single-image output' conflicts with the 'count' parameter (max 4), creating ambiguity about panel behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences that front-load the purpose and key distinction. Every sentence provides essential information without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite no output schema, the description fails to clarify the inconsistency between 'single-image output' and the 'count' parameter allowing up to 4 panels. This creates confusion about what the tool actually returns when count > 1, making it incomplete for agent reasoning.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, providing baseline 3. The description adds meaning beyond the schema: explains 'wait' default and task-ID behavior, 'count' billing, 'model' examples, and 'reference_images' structure with fields like role/strength. This adds value over the schema alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates an image via a specific node type (GENERATE_STORYBOARD) and explains it is identical to generate_image, distinguishing it by classification. This provides a specific verb+resource and differentiates from a sibling tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises to use generate_image unless downstream requires the GENERATE_STORYBOARD classification. This gives clear when-to-use and when-not-to-use guidance, with an alternative specified.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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