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list_inventory_variants

Read-onlyIdempotent

List inventory variants/SKUs sorted by name, filtered by product, category, or search query.

Instructions

List inventory variants/SKUs sorted by name. Optionally scope to product by ID/exact name; category can disambiguate product names. query filters variant names and SKUs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNoa string that will be trimmed
productNoa string that will be trimmed
categoryNoa string that will be trimmed
limitNoMaximum number of variants to return (default: 50).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYesThe successful tool result. The same value is also serialized as JSON in the text content for clients that do not read structuredContent.
warningsNoOptional agent-visible warnings about degraded result fidelity. Omitted when the server returned the documented happy-path payload.
Behavior4/5

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

Annotations declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, consistent with listing. Description adds sorting by name and filtering behavior, but doesn't detail pagination (limit parameter in schema suffices). No contradictions.

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 concise sentences front-loaded with main purpose. No redundant words, directly states core function and optional scoping/filtering.

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?

With output schema present, description doesn't need return value details. Covers core listing, sorting, and filtering. Could mention default limit or max from schema, but not critical.

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

Parameters4/5

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

Schema covers 100% of parameters with descriptions. Description adds context on how parameters interact: product and category scope, query filters names/SKUs, enhancing understanding beyond schema.

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 lists inventory variants/SKUs sorted by name, with optional filters for product and category, and a query filter. This distinguishes it from sibling tools like get_inventory_variant or list_inventory_products.

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?

Provides guidance on optional parameters (product, category, query) and their roles. However, it doesn't explicitly suggest when to use this tool over alternatives, such as using get_inventory_variant for a single variant.

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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