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genart-dev

genart-mcp

by genart-dev

design_create_atmosphere

Generate multi-layer atmospheric scenes from selectable recipes such as winter-storm, firefly-night, or autumn-forest, with an optional seed for reproducible layer placement.

Instructions

Create a multi-layer atmospheric scene from a named recipe. Recipes: winter-storm (snow + fog + haze), autumn-forest (leaves falling + ground + mist), misty-morning (mist + dust), firefly-night (fireflies + fog), spring-meadow (petals + pollen + wildflowers), dusty-ruins (dust + pebbles + steam).

Input Schema

NameRequiredDescriptionDefault
seedNoBase seed for all layers.
recipeYesAtmosphere recipe name.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose the concrete output of each recipe (snow + fog + haze, etc.), which is genuinely useful behavioral context beyond the enum names. However, it omits whether existing atmosphere layers are replaced or added to, whether the operation is destructive, and how the seed influences the result.

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

Conciseness4/5

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

Two sentences, front-loaded with the action and scope, followed by the recipe catalog. The parenthetical layer lists are dense but each one maps directly to a valid enum value, so nothing is wasted; a tighter format would be a bulleted list, but this is close to optimal.

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

Completeness4/5

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

For a two-parameter creation tool with no output schema and full schema coverage, the description covers what an agent needs to pick a recipe and call it. The remaining gap is the effect on existing scene state and the return value, which is minor given the tool's simplicity.

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%, so the baseline is 3, but the description earns above that by explaining what each recipe value actually composes — semantic content the enum alone does not convey. The seed parameter is left entirely to the schema ('Base seed for all layers'), which is acceptable at full coverage.

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

Purpose4/5

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

States a specific verb and resource ('Create a multi-layer atmospheric scene from a named recipe') and enumerates the six recipes with their constituent layers, so the agent knows exactly what will be produced. It does not name or contrast with the obvious siblings (design_add_atmosphere, design_add_fog_layer, design_list_atmosphere_presets), so it falls short of full sibling differentiation.

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

Usage Guidelines3/5

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

Usage is only implied: the word 'recipe' and the layer breakdown suggest this is the one-shot composite option versus single-layer siblings like design_add_fog_layer or design_add_mist. No explicit 'use this when…' or 'use X instead when…' statement is present, and nothing tells the agent whether this is additive to an existing scene or a fresh setup.

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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