Skip to main content
Glama

Smasher Studio — AI Fashion Design

Generate Multi-Angle Views

generate_multi_angle

Generate coordinated multi-angle views of a garment (front, back, side, etc.) with consistent style across all angles. Uses a best-in-class multi-model image chain with automatic fallback. Costs 4 credits per angle.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
styleNoPhotography style: product_shot (catalog), on_model (lifestyle), flat_lay (social), editorial (magazine)product_shot
anglesYesCamera angles to generate: front, back, side_left, side_right, three_quarter, detail_close
promptYesBase garment prompt WITHOUT angle direction (added automatically per view)
qualityNoImage quality: standard (fast), hd (recommended), ultra (maximum detail)hd
backgroundNoBackground description: "pure white seamless", "gradient beige to cream"
aspect_ratioNoAspect ratio: 1:1 (square), 4:3 (landscape), 3:4 (portrait), 16:9 (wide), 9:16 (stories)1:1

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It adds useful context about using a multi-model image chain with automatic fallback and the cost of 4 credits per angle, which are not visible in the schema. However, it does not describe potential delays, failure modes, or side effects.

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?

The description is three sentences, each carrying distinct value: what it does, how it works (model chain), and cost. No fluff or repetition of schema fields, making it concise and well-structured.

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?

The description covers the tool's core purpose, mechanism, and cost, and the schema fully documents all parameters. It does not explain the return format (no output schema exists), but for a generation tool that likely returns standard image results, the given context is sufficient for an agent to invoke it correctly.

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 description coverage is 100%, so the baseline is 3. The description's examples of angles ('front, back, side, etc.') add little beyond the schema's enum, and it does not explain parameter interactions or formatting beyond what the schema already states. It adds no significant parameter semantics.

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's action ('Generate coordinated multi-angle views of a garment') and specifies the resource (garment) and angle types (front, back, side, etc.). It also mentions consistent style, which distinguishes it from generic image generation tools.

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

Usage Guidelines4/5

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

The description clearly indicates when to use the tool (when multi-angle views are needed) and emphasizes coordination, but it does not explicitly name alternative tools or provide when-not-to-use guidance. The context is clear, yet exclusions or comparisons with siblings are absent.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.1/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: credit checking, video status polling, colorway generation, fabric simulation, image generation, video generation, multi-angle generation, and collection listing. No two tools overlap in function, making selection unambiguous.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern: check_*, generate_*, list_*. This uniformity makes the API predictable and easy to navigate.

Tool Count5/5

With 8 tools, the server is well-scoped for its AI fashion design purpose. Each tool contributes a distinct capability, and the set is neither bloated nor sparse.

Completeness4/5

The core generation workflows (image, video, variants, multi-angle) are well covered, including async status checking. Minor gaps exist, such as no collection creation/update/delete or asset retrieval, but these do not break the primary generation flow.

Resources