Skip to main content
Glama

aaddyy_halloween_costume_generator

Generate personalized Halloween costume designs with AI. Create individual, couple, family, or group concepts by choosing themes, eras, styles, and accessories.

Instructions

Generate unique and creative Halloween costume designs using AI. Create personalized costumes for individuals, couples, families, or groups with customizable themes, styles, and accessories. (~6 credits)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
eraNo
themeNo
promptYes
gender_fitNo
num_imagesNo
output_typeNo
aspect_ratioNo
costume_typeNo
photo_uploadNo
color_paletteNo
output_formatNo
character_moodNo
creativity_levelNo
inspiration_imageNo
group_coordinationNo
material_preferenceNo
body_type_adaptationNo
accessory_preferencesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.2

TDQS

C2.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries full behavioral burden, yet it only discloses the credit cost (~6 credits). It says nothing about latency, what the output looks like, whether photo_upload is processed, or what happens on partial failures. Credit cost is a genuinely useful trait but alone is thin.

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 tight sentences, front-loading the core action and following with capability scope, closing with the cost note. No filler, though the second sentence partially restates the first.

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?

For an 18-parameter tool with no output schema and no annotations, the description is far too thin. It omits return format, how images are delivered, whether photo_upload/inspiration_image are URLs or files, and what the required 'prompt' should contain — all material for correct invocation.

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

Parameters2/5

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

Schema coverage is 0% and 18 parameters exist, so the description must carry the load. It gestures at 'themes, styles, and accessories' (mapping loosely to theme/accessory_preferences) and subject types (costume_type), but leaves num_images, photo_upload, inspiration_image, creativity_level, group_coordination, body_type_adaptation, and output_type entirely unexplained.

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?

The description states a specific verb ('Generate') and resource ('Halloween costume designs') and enumerates the supported subject scopes (individuals, couples, families, groups). This is clear enough to distinguish it from generic siblings like aaddyy_image_generator, though it doesn't explicitly name an alternative.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no prerequisites, and no comparison against the many sibling image generators (image_generator, nano_banana, ghibli_generator). The agent must infer that this is the Halloween-specific option purely from the name.

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