AutoID

Get live AutoID offers by condition

get_product_offer

Returns the current authoritative commercial offer data for one exact SKU. A single SKU may expose offers.new, offers.refurbished and offers.used with independent price and stock. Refurbished/Used may also include grade, warranty, note, Google eligibility, professional reconditioning/refurbisher and component-condition fields. ALWAYS use this tool before answering current price, stock, availability or delivery questions. The MCP never manufactures a condition: if the canonical API has not exposed offers.refurbished/offers.used, condition requests explicitly report source_support=false instead of treating the condition as unavailable.

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_product_offer"
  }
}

Input Schema

Name	Required	Description	Default
`sku`	Yes	Exact AutoID product SKU.
`condition`	No		all

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 14, 2026

addedInput schema / properties / condition

Added value: +{
+  "default": "all",
+  "enum": [
+    "all",
+    "new",
+    "refurbished",
+    "used"
+  ],
+  "type": "string"
+}

First observedSep 11, 2026

TDQS

A4.7/5.0

Behavior5/5

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

With no annotations provided, the description carries the full burden and delivers extensively. It discloses that offers are independent per condition, lists optional fields for refurbished/used, and crucially explains the source_support=false behavior instead of treating a missing condition as unavailable. This goes well beyond a basic 'returns offers' statement.

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 four dense sentences with no filler. The main purpose is front-loaded, and every additional sentence adds unique value: condition structure, field details, usage directive, and error behavior. It is well organized and efficient.

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

Completeness5/5

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

There is no output schema, so the description must convey the return shape, and it does. It enumerates the offer groups a SKU may expose, the additional fields for refurbished/used, and the exact behavior when the canonical API lacks a condition. For a single-SKU lookup tool, nothing critical 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 description coverage is only 50%: the 'sku' parameter is documented, but 'condition' lacks a description. The description compensates by explaining the condition dimension (new, refurbished, used) and the edge-case behavior for unsupported conditions. It does not fully map the parameter to its 'all' default or enum mechanics, so it stops short of a 5.

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: 'Returns the current authoritative commercial offer data for one exact SKU.' It clearly distinguishes itself from sibling product tools by focusing on offers, price, stock, and condition-specific data, making it easy for an agent to select it over get_product or get_product_group.

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 explicit when-to-use guidance: 'ALWAYS use this tool before answering current price, stock, availability or delivery questions.' This is strong usage context, though it does not name sibling alternatives or explicitly state when not to use the tool, so it misses the full 5.

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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