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microsoftstore_recommended

Fetch the Microsoft Store's default recommendation shelf with no search query. Set country or locale to return public recommendations before anyone types.

Instructions

Get the Microsoft Store's default recommendation shelf. Returns the store's default, query-less "Recommended for you" shelf -- the same recommendations the search box shows before a caller types anything. No query parameters beyond region/locale. Credential-free public Microsoft Store data, read directly from the store's own zero-state search API.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
localeNoDisplay locale (BCP-47)
countryNoStore country/region code (ISO-2)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.5

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that the tool is credential-free, uses public Microsoft Store data, and reads directly from the store's zero-state search API, which implies a read-only operation. It also clarifies the scope (default shelf) and parameter limits, adding useful behavioral context beyond the schema.

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 three sentences, each adding value: purpose, what is returned, and behavioral notes (no query params, credential-free, read directly). It is front-loaded with the core action and contains no redundant or filler content.

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 simple tool with no required parameters and no output schema, the description is complete. It explains the tool's purpose, return semantics (recommendation shelf), and operational details (credential-free, public, read-only). It does not specify the exact return structure, but that is not essential given the tool's simplicity and lack of an output schema.

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 coverage is 100%—both parameters (locale, country) have descriptions. The description only mentions 'region/locale' without adding detail beyond the schema. Since the schema already documents the parameters well, the description adds minimal extra value here, meeting the baseline for high coverage.

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: 'Get the Microsoft Store's default recommendation shelf.' It clearly identifies what the tool returns—the query-less 'Recommended for you' shelf—and distinguishes it from search-related siblings by noting it is the zero-state shelf, making its purpose unambiguous.

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 provides clear context: it is the default, query-less recommendation shelf, the same one shown before typing in the search box. It implies this is for when no query is needed, and explicitly states there are no query parameters beyond region/locale. It does not name alternative tools explicitly, but the usage context is well-defined.

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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