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Find Low Stock Across Shopify Stores

shopify_low_stock_report
Read-onlyIdempotent

Identify active product variants at or below an inventory threshold across selected stores. Get a clear breakdown of low, zero, and negative stock to manage replenishment.

Instructions

Find every active product variant at or below an inventory threshold across selected stores. Separates low, zero, and negative inventory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
storesYesOne to one hundred configured store aliases
thresholdNoMaximum aggregate inventory quantity to include.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.6.0
    • changedInput schema / properties / stores / description
      Previous value: -"One to ten configured store aliases"New value: +"One to one hundred configured store aliases"
    • changedInput schema / properties / stores / maxItems
      Previous value: -10New value: +100
  2. Addedv1.5.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds useful behavioral context beyond annotations: it targets only active variants and explicitly separates low, zero, and negative inventory, which informs the agent about result categorization.

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 with no filler. The core behavior is front-loaded, and the inventory categorization detail is placed immediately after, making it easy to parse quickly.

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 only two simple parameters and strong annotations, the description is mostly complete for invocation. There is no output schema, but the description compensates by specifying the result categorization ('low, zero, and negative inventory') and the target scope ('every active product variant across selected stores'). A more detailed return format would be helpful but is not essential.

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 both 'stores' and 'threshold' are already documented with clear meanings. The description adds no new parameter syntax or format details beyond the schema, so the baseline of 3 is appropriate.

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 states a specific verb and resource: it 'Find[s] every active product variant at or below an inventory threshold across selected stores.' It also adds unique behavior by separating low, zero, and negative inventory, which differentiates it from general inventory lookup tools like shopify_get_inventory_levels.

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 gives clear context for when this report is appropriate: when the agent needs active product variants across multiple stores at or below a threshold. It does not explicitly name alternatives or exclusions, but the cross-store and threshold scoping make the intended usage apparent.

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