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get_inventory

Get inventory analytics. Reports: summary (activeProducts count, totalVariants, outOfStock variant count, lowStock variant count with >0 and ≤10 units, totalUnits, active locations count), low_stock (products needing reorder — threshold defaults to 10 units), out_of_stock (zero-inventory variants), by_location (per-warehouse breakdown with location name, total SKUs tracked, units on hand).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of products (default: 20)
reportYesReport type
_offsetNoPagination offset. If a response includes _pagination.hasMore=true, use _offset to fetch the next page.
thresholdNoFor low_stock: stock level threshold (default: 10)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. Added

TDQS

A3.9/5.0
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. It discloses the output content of each report and the threshold default, which is genuine value, but it never confirms read-only/no-side-effect behavior, permissions, or pagination semantics beyond what the schema already implies.

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?

The purpose is front-loaded in the first clause, then the report details follow in a structured enumeration. It is dense but every clause maps to an actual report or parameter, with little waste.

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 tool with no annotations and no output schema, the description does substantial work by describing what each report returns. An agent has enough to call it correctly; only cross-tool routing guidance is missing.

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 coverage is 100% (baseline 3), and the description adds real meaning: it explains what each enum value means and defines low_stock's threshold. It enriches the terse 'Report type' schema entry rather than merely restating it.

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 opens with a specific verb+resource ('Get inventory analytics') and then enumerates all four report types with the exact metrics each returns. An agent can tell precisely what this tool does and how it differs from adjacent analytics tools like get_product_analytics or get_velocity.

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

Usage Guidelines3/5

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

It implies usage by defining each report (summary, low_stock, out_of_stock, by_location) so the agent can pick the right report param, but it never states when to choose this tool over siblings or any prerequisites/exclusions. Usage is implied rather than guided.

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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