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Query inventory

query_inventory
Read-only

Returns paginated inventory listing data for a single store. FBA-specific fields are populated only for AFN inventory and are null for MFN inventory when not applicable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skusNoComma-separated SKU filters, up to 100 values. Omit to include all SKUs.
asinsNoComma-separated ASIN filters, up to 100 values. Omit to include all ASINs.
limitNoMaximum number of items to return. Defaults to 100 and cannot exceed 100.
offsetNoZero-based pagination offset.
storeIdYesStore ID from the Stores API, formatted as sellerId:marketplaceId.
salesChannelNoOptional inventory fulfillment channel filter. Allowed values are AFN and MFN. Omit to include all channels.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

The annotations already declare this as a safe read-only operation. The description adds useful behavioral context beyond annotations: results are paginated and FBA-specific fields are populated only for AFN inventory and null for MFN when not applicable.

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 two tightly written sentences with zero waste. The core behavior is front-loaded, and the second sentence adds a specific, relevant caveat about FBA fields.

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 tool has a rich input schema, full parameter descriptions, annotations, and an output schema, so the description need not explain return values or every parameter. It adequately covers pagination and AFN/MFN field behavior, though it could mention when to prefer sibling tools like query_inventory_alerts.

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 parameters are already well documented. The description adds a small amount of meaning by explaining AFN/MFN-specific null behavior, which relates to the salesChannel filter, but it does not add syntax or filtering details beyond the schema.

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?

The description states a specific verb and resource: returns paginated inventory listing data. It also scopes the operation to a single store, which helps distinguish it from broader or alert-oriented siblings, but it does not explicitly differentiate it from query_inventory_alerts or inventory_risk_review.

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

Usage Guidelines2/5

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

The description implies that this tool retrieves inventory listing data, but it provides no explicit when-to-use guidance, exclusions, or alternative tools. An agent must infer that query_inventory_alerts should be used for alerts and inventory_risk_review for risk analysis.

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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