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Get product

get_product
Read-onlyIdempotent

Get structured product price intelligence by product_id (e.g. demo_iphone_15_pro or prod_xxx from a completed job). On failure, returns a structured error object with fields error.code, error.message, error.http_status, error.retry_recommended, and error.retry_after_seconds.

Input Schema

NameRequiredDescriptionDefault
product_idYesPublic product ID

Output Schema

NameRequiredDescriptionDefault
nameYes
shopYes
statusNo
previewNo
currencyYes
product_idYes
product_urlNo
current_priceNo
last_checked_atNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • removedInput schema / additionalProperties
      Removed value: -false
    • changedOutput schema / additionalProperties
      Previous value: -trueNew value: +{}
  2. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive). The description adds genuine behavioral context by disclosing the structured failure object and its retry-related fields (error.code, error.retry_recommended, error.retry_after_seconds), which is useful for an agent deciding whether to retry.

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 sentences, front-loaded with the primary operation and scope, followed by failure behavior. No filler or repetition of schema/annotation content.

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?

For a single-parameter read-only tool with an output schema and full annotation coverage, the description provides what is needed: the purpose, ID examples, and structured error behavior. Return-value details are appropriately left to the output schema.

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%, so the single product_id parameter is already documented. The description adds value by giving concrete examples of the ID format ('demo_iphone_15_pro or prod_xxx from a completed job'), which clarifies meaning beyond the schema's generic 'Public product ID'.

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?

The description states a specific verb and resource: 'Get structured product price intelligence by product_id'. It is clearly distinct in kind from sibling tools like search_products or get_price_history, though it does not explicitly name those alternatives to route the agent.

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?

Usage is only implied: the agent should use it when it already has a product_id from a completed job or a known demo ID. The description does not say when to prefer search_products or get_price_history instead, nor does it state exclusions.

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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