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microsoftstore_related

Find products related to a Microsoft Store item by its product ID, with pagination and optional product type auto-resolution.

Instructions

Get products related to a Microsoft Store product. Returns products related to a seed product id, paginated. product_type must match the seed product's own media type (apps -> Application, games -> Game, passes -> Passes) -- any other value is rejected upstream. Omit product_type to have it resolved automatically from product_id via one extra lightweight lookup; pass it explicitly to skip that lookup.

Input Schema

NameRequiredDescriptionDefault
pageNo1-based page number
localeNoDisplay locale (BCP-47)
countryNoStore country/region code (ISO-2)
page_sizeNoRelated products per page (max 24)
product_idYesSeed Microsoft Store product id
product_typeNoThe seed product's own type. Omit to auto-resolve from product_id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.5

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose real behavior: paginated results, upstream rejection for mismatched product_type, and an extra lookup when product_type is omitted (a latency tradeoff). It does not mention auth requirements or the shape of returned products, leaving some gaps.

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?

Three tight sentences, front-loaded with the core action and pagination, then the critical product_type constraint and the auto-resolve tradeoff. Every sentence carries actionable information with no padding.

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?

For a 6-parameter related-products tool with no output schema and no annotations, the description covers purpose, pagination, and the tricky product_type semantics well. It stops short of describing returned product fields or error behavior beyond product_type rejection.

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 baseline is 3, but the description adds value beyond the schema: it explains the apps->Application / games->Game / passes->Passes mapping and that a mismatched value is rejected upstream, plus the performance cost of omitting product_type. Page/page_size/locale/country semantics are left to the schema.

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 opens with a specific verb+resource: 'Get products related to a Microsoft Store product', and clarifies it's a paginated seed-based lookup. It does not, however, explicitly differentiate itself from siblings like microsoftstore_recommended or microsoftstore_product, which an agent might confuse with 'related'.

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?

It gives concrete usage guidance for the product_type parameter: pass it explicitly to skip the lookup, omit it to auto-resolve via an extra lightweight call. It does not say when to prefer this tool over microsoftstore_recommended or microsoftstore_search, so alternative-selection guidance is absent.

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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