Skip to main content
Glama

Save a generation's styling as a reusable template

create_template_set

Save the styling details from a finished fashion photo, then reuse them to put a new garment on the same model and setting.

Instructions

Saves the fashion_model/venue/pose/shotType/stylePreset/ratio from a completed generation (sourceMediaId) as a named preset. Reuse it later via create_generation's templateSetId to put a NEW garment on the exact same model/venue/pose.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
poseNo
labelYesA name for this preset, e.g. 'Studio white, model A, 3/4 pose'.
ratioNo
imagesNoRequired if sourceMediaId is omitted.
toolIdNoRequired if sourceMediaId is omitted. One of: virtual_model, outfit_photo, pro_studio, jewelry_on_model, clothing_ecom_pack, jewelry_ecom_pack.
shotTypeNo
stylePresetNo
sourceMediaIdNoA completed generation's id (from create_generation/get_generation) to capture styling from.
Behavior3/5

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

With no annotations, the description carries the behavior burden. It clearly implies persistence by 'Saves... as a named preset' and clarifies that the garment is not captured ('NEW garment'). However, it does not disclose overwrite/collision behavior, permissions, or the response shape.

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 sentences, front-loaded, and free of filler. The dense field list is justified because it tells agents exactly what gets persisted.

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 8-parameter tool with a nested object, no annotations, and no output schema, this is incomplete. The description presents sourceMediaId as the only path, leaving the images+toolId path to schema hints, and never states what the tool returns.

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?

The description adds useful meaning by grouping the captured styling fields and linking sourceMediaId to a completed generation. But it omits the alternative images+toolId construction path entirely, and with 50% schema coverage it does not fully compensate for undocumented parameters like pose, ratio, shotType, and stylePreset.

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 names a specific action ('Saves... as a named preset'), a specific input ('from a completed generation (sourceMediaId)'), and the exact fields captured. It also differentiates this from create_generation by explaining how the saved preset is reused via templateSetId.

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?

It gives a clear workflow: use this after a completed generation, then use the resulting templateSetId in create_generation with a new garment. It does not explicitly list when-not-to-use or contrast with list/delete template set siblings, so it falls just short of an explicit routing guide.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/fashiolabs/fashio-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server