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Check Inventory

check_inventory

Check stock for a product SKU and return available quantity and in-stock status without changing inventory.

Instructions

Check stock for a SKU.

Example in stock: SKU-1001. Example out of stock: SKU-1002. Returns stock_qty and in_stock. Does not change inventory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
product_idYesAlphanumeric product SKU (hyphens ok), e.g. SKU-1001

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden, and it does disclose the key trait that this is a non-mutating read ('Does not change inventory'). It stays silent on other behavior an agent may need: what happens for an unknown or malformed SKU, whether the result is cached/eventually consistent, and any auth requirements.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short lines with the purpose front-loaded and no padding. The paired example SKUs are marginally redundant given the schema already supplies SKU-1001, but they are cheap and aid quick testing.

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 one-parameter read tool with a full output schema and complete param documentation, the description covers the essentials: what it reads and that it does not mutate. Only the unknown-SKU behavior is left unaddressed, a minor gap at this complexity level.

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 coverage is 100% for the single product_id parameter, so the schema already documents format and gives the SKU-1001 example. The description's example SKUs repeat that same example rather than adding syntax, validation, or edge-case meaning, so the baseline 3 applies.

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 ('Check stock for a SKU'), which is enough to separate it from siblings like add_to_cart, place_order, and get_order_details. It does not, however, draw a line against get_product_details, which plausibly also exposes stock information, so sibling differentiation is incomplete.

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 never says when to prefer this tool over get_product_details or search, nor does it state any preconditions. The in-stock/out-of-stock example SKUs hint at how to exercise the tool but are not usage guidance.

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