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Create free try-on preview

create_preview_job

ONE free on-model preview per store, no account needed. Pass the store and one of its listing photo URLs (from an audit_store work order) to generate a free 2K on-model try-on photo — the taste before buying credits. Poll with get_preview_status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoPreset model (default woman)
store_urlYesThe store the photo belongs to (same as audit_store)
product_typeNoTop | Bottom | Dress | Full-body (default Top)
garment_image_urlYesA listing photo URL from that store (audit work order image_url)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
pollNoHow to retrieve the result
errorNoMachine-readable error code (only present on failures)
storeNoNormalized store host the preview belongs to
statusNoInitial job state (usually queued)
messageNoHuman-readable explanation of the failure
preview_idNoPreview job UUID — poll with get_preview_status

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint false), the description discloses key behavioral constraints: one free preview per store, no account required, and the need to poll with get_preview_status. It also clarifies that the generating is free and produces a 2K image, adding meaningful context for the agent.

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 extremely concise—two sentences—and front-loaded with the most critical constraint (one free preview per store). Every word adds value, with no filler or repetition of schema details.

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

Completeness5/5

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

Given the tool has 4 parameters (2 required) and an output schema, the description covers the prerequisite (audit_store work order), the free/limit constraint, and the follow-up polling step. It is sufficiently complete for an agent to select and invoke the tool correctly without additional context.

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 adds limited extra meaning beyond the schema, mainly connecting store_url and garment_image_url to an audit_store work order, which the schema already partially states. No significant new parameter-level details are provided.

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 creates a free 2K on-model try-on preview, specifying the exact inputs (store and listing photo URL) and distinguishing it from the paid create_tryon_job and the polling get_preview_status. The phrase 'taste before buying credits' reinforces its specific purpose.

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 conveys when to use the tool ('taste before buying credits') and provides usage context (one free per store, no account needed, from an audit_store work order). However, it does not explicitly name the paid alternative or state when not to use it, so it falls short of explicit when/when-not guidance.

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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TDQS

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct function: auditing a store, creating preview/tryon jobs, polling their statuses, checking credits, and getting seasonal guides. The preview vs tryon separation is clear, and audit_store explicitly references create_tryon_job, avoiding confusion.

Naming Consistency5/5

All tool names follow a strict verb_noun pattern (audit_store, create_preview_job, create_tryon_job, get_credits_balance, get_job_status, get_preview_status, get_seasonal_guide). Verb choices are consistent and the pattern is immediately predictable.

Tool Count5/5

Seven tools is well-scoped for this domain. Each tool serves a distinct part of the workflow—audit, preview, tryon generation, status polling, credit management, and seasonal guidance—with no redundancy or unnecessary extras.

Completeness5/5

The tool set covers the full lifecycle for both preview and tryon workflows: audit to identify needs, create jobs, poll status, and manage credits. The seasonal guide provides context for the audit. There are no obvious dead ends or missing operations for the stated purpose.

Resources