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by RPasquale
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Python
Remote

square_get_inventory

Read-onlyIdempotent

Fetch current inventory counts for Square catalog items, optionally filtered by specific locations. Get accurate stock levels to manage availability.

Instructions

Fetch Square inventory counts for one or more catalog items.

Args: catalog_object_ids (required): Catalog object IDs to fetch inventory counts for. location_ids: Optional location IDs to restrict counts to. project_id: Authenticated Project UUID. project_ref: Exact project correlation reference. connector_account_ref: Project-bound connector account alias. idempotency_key: Stable business-action identity. effect: Required and must be read; Spring verifies it. approval_ref: Approved platform task UUID when resuming a write.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
effectYes
project_idNo
project_refNo
approval_refNo
location_idsNo
idempotency_keyNo
catalog_object_idsNo
connector_account_refNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed7 schema fields changedv0.1.1
    • addedInput schema / properties / approval_ref
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Approval Ref"
+}
    • addedInput schema / properties / connector_account_ref
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Connector Account Ref"
+}
    • addedInput schema / properties / effect
      Added value: +{
+  "const": "read",
+  "title": "Effect",
+  "type": "string"
+}
    • addedInput schema / properties / idempotency_key
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Idempotency Key"
+}
    • addedInput schema / properties / project_id
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Project Id"
+}
    • addedInput schema / properties / project_ref
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Project Ref"
+}
    • addedInput schema / required
      Added value: +[
+  "effect"
+]
  2. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

The annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description adds no additional behavioral context beyond the word 'Fetch', which is consistent with the annotations but provides no extra details about side effects, rate limits, or data access.

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 a single clear sentence followed by a neatly formatted argument list. There is no redundant or filler content, and the structure makes the tool's purpose and parameters immediately scannable.

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?

Given the tool's simplicity and the presence of an output schema, the description sufficiently covers the input side. It does not describe return values, but that is acceptable since an output schema is declared. It also doesn't clarify edge cases like empty results, but that is not required for basic invocation.

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?

The description explains all eight parameters, including domain-specific ones like 'catalog_object_ids' and 'location_ids', giving clear meaning beyond the schema titles. However, the generic platform parameters (e.g., project_ref, connector_account_ref, effect) are described only with standard boilerplate phrases, not deep context.

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 action ('Fetch') and the resource ('Square inventory counts') and specifies the scope ('for one or more catalog items'). This distinguishes it from sibling tools like square_get_catalog_item or square_list_payments.

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 provides no guidance on when to use this tool versus alternatives such as square_search_catalog or square_get_catalog_item. It does not mention any conditions, exclusions, or explicit 'use this instead when...' instructions.

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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