Velox TriFit: Virtual Try-On API

Create one guest virtual try-on

create_try_on

Destructive

Generate a DressMe virtual try-on from the user’s personal photo and clothing reference only after their explicit request and permission. In ChatGPT pass both attached image files; in Codex pass the two asset IDs returned by completed private uploads. Use one method, not both. Consumes one session attempt and one shared daily attempt. One attempt per guest session, ten per day across all guests. Do not automatically retry or bypass limits. Returns a receipt; get_try_on retrieves its status/result.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "consent": "<consent>"
    },
    "name": "create_try_on"
  }
}

Input Schema

Name	Required	Description	Default
`consent`	Yes
`garment_image`	No
`personal_image`	No
`product_asset_id`	No
`personal_asset_id`	No

Output Schema

Name	Required	Description	Default
`error`	No
`jobId`	No
`status`	Yes
`timing`	No
`createdAt`	Yes
`requestId`	Yes
`updatedAt`	Yes
`failureCode`	No
`queuePaused`	No
`failureStage`	No
`queuePosition`	No
`resultAssetId`	No
`durationSeconds`	No
`failureHttpStatus`	No
`submissionAttempted`	No
`minimumStartGapSeconds`	No

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 24, 2026

TDQS

A4/5.0

Behavior4/5

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

Adds real context beyond the annotations: consumption of one session attempt and one shared daily attempt, a 1-per-session / 10-per-day cap, non-retry guidance, and that the call returns a receipt rather than a result. That explains why destructiveHint=true matters (attempts are burned), though it never says what is destroyed or whether the uploads remain usable after a failure.

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?

Six short sentences, front-loaded with the permission precondition, then invocation method, then cost limits, then the follow-up pointer to get_try_on. No filler and every sentence carries operational information.

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 metered, consent-gated generation tool it covers preconditions, both invocation modes, quota cost, retry policy, and the receipt/get_try_on workflow, and an output schema already documents the return shape. The remaining hole is the undocumented required 'consent' boolean and the absence of sibling differentiation.

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 0% across 5 parameters including two nested image objects, so the description has to carry weight. It does clarify the crucial mutual exclusivity the schema cannot express (images in ChatGPT vs. the two asset IDs in Codex, 'use one method, not both'), but it never explains the consent field, nor why download_url and file_id are jointly required.

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 ('Generate a DressMe virtual try-on') plus the inputs it works from, which is far more than a restated name. It does not, however, differentiate itself from the sibling create_trifit_try_on, so an agent must infer which try-on flavor applies.

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?

Gives an explicit precondition ('only after their explicit request and permission') and explicit exclusions ('Do not automatically retry or bypass limits'), plus environment-specific invocation routes. Missing is any routing advice versus create_trifit_try_on or the upload/prepare siblings named in the tool list.

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

All Velox TriFit: Virtual Try-On API tools Inspect

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