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Get inventory item

get_inventory_item
Read-onlyIdempotent

One inventory item by SKU.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "sku": "<sku>"
    },
    "name": "get_inventory_item"
  }
}

Input Schema

NameRequiredDescriptionDefault
skuYesThe item's SKU.
fieldsNoWhich fields to return. Leave out for the usual ones: sku, name, description, quantity, unit, price, cost, category, low_stock_threshold, location, images, created_at, updated_at.
project_idNoWorkspace to work in (from list_projects). Leave out for the default one.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior2/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and closed-world scope, so the safety profile is fully covered elsewhere. The description adds nothing on top: not what happens for an unknown SKU (error vs empty), nor that missing fields fall back to a default set.

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

Conciseness3/5

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

Four words with zero waste and the key discriminator ('by SKU') front-loaded, but the terseness crosses into under-specification rather than efficient density. Nothing is padded, yet nothing is earned beyond the name.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple, read-only, single-entity lookup with full schema coverage and rich annotations, the minimal text is close to adequate. The gap is behavioral edge cases (not-found handling, default field projection) that neither annotations nor schema express.

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 sku, fields and project_id are already documented in the schema, including the default field-set behavior and the list_projects reference. The description itself adds no parameter meaning beyond that, 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?

'One inventory item by SKU' names a specific resource and its lookup key, which separates it from list_inventory and get_inventory_overview without the agent needing to open the schema. It is a fragment rather than a sentence, but the retrieval intent is unambiguous.

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 phrase 'by SKU' only hints at when to reach for this tool. There is no explicit statement of when to use it versus list_inventory (browsing) or get_inventory_overview (aggregate), and no prerequisites such as needing a valid SKU from a prior listing call.

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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