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lunaar_studio_tryon

Create virtual try-on images by combining a person photo with one or more garments. Supports single item, combo, layer, summer swimwear, and kids catalog modes.

Instructions

Virtual try-on. SingleItem (10 credits): person + 1 garment. Combo (15): person + 2-6 garments. Layer (15): person + 3 stacked garments. Summer (15): swimwear with environment. Kids (15): kidswear catalog — 1..N product images on a fully AI-generated child model (no PersonImage); requires kidsGender, kidsAgeRange, and kidsProductCategory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYes
fitTypeNo
kidsPoseNokids mode only — optional. Omit to let the model choose.
kidsGenderNokids mode only — required.
aspectRatioNoOptional output aspect ratio. Backend resolves the concrete pixel size; null/omitted lets the model auto-pick.
dressLengthNo
kidsAgeRangeNokids mode only — required.
topImagePathNo
maskImagePathNo
dressImagePathNo
kidsBackgroundNokids mode only — optional. Omit to let the model choose.
shoesImagePathNo
bottomImagePathNo
layer1ImagePathNo
layer2ImagePathNo
layer3ImagePathNo
personImagePathNoRequired for single_item / combo / layer. Not used for summer or kids.
backgroundSeasonNo
clothingCategoryNosingle_item only.
clothingImagePathNosingle_item only.
swimSuitImagePathNo
accessoryImagePathNo
bikiniTopImagePathNo
outerwearImagePathNo
kidsProductCategoryNokids mode only — required.
menSwimwearImagePathNo
bikiniBottomImagePathNo
kidsProductImagePathsNokids mode only — 1..N product image paths. For two_piece_set, supply at least 2.
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses credit costs and mode-specific behavior (e.g., 'Kids' uses AI-generated child model, no PersonImage). However, it does not mention failure modes, rate limits, or the response structure, leaving gaps in transparency.

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?

The description is relatively concise given the complexity, with each sentence adding distinct information (modes, credits, parameter conditions). It is front-loaded with the core purpose. Minor improvements could include bullet points for clarity, but it remains efficient.

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

Completeness3/5

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

With 28 parameters, no output schema, and moderate schema coverage, the description provides essential mode-specific context but omits details on return format, error handling, or parameter interrelationships beyond mode requirements. It is adequate but not fully comprehensive.

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

Parameters3/5

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

Schema coverage is low (36%), but the description adds value by explaining mode dependencies and required parameters (e.g., for 'Kids': kidsGender, kidsAgeRange, kidsProductCategory). However, many parameters (e.g., fitType, dressLength) are not elaborated beyond the schema, and the description does not fully compensate for the coverage gap.

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 identifies the tool as 'Virtual try-on' and enumerates five specific modes with distinct credit costs and requirements. This specificity distinguishes it from sibling tools like lunaar_jewelry_tryon and lunaar_glasses_tryon, which cover different domains.

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?

The description implies usage by detailing modes (e.g., 'SingleItem', 'Combo') but does not explicitly compare this tool to alternatives or provide scenarios where it is preferred. Some mode-specific guidance is given (e.g., 'Kids' requires certain parameters), but no when-to-use or when-not-to-use statements are present.

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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