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Mall Store Directory

stores_by_category

List stores by category, optionally filtered by country.

Categories are multilingual (RO/EN) and hierarchical
('Fashion' matches 'Women's Fashions' and 'Shopping / Modă').
Diacritic-insensitive substring match.

Args:
    category: Category name or fragment (e.g. 'Fashion', 'Food Court', 'Telecom').
    country: Optional country filter: ro, us, gb, hu.
    max_results: Maximum number of stores to return (1-100).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countryNo
categoryYes
max_resultsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries full behavioral burden and reveals non-obvious traits: hierarchical expansion ('Fashion' matches 'Women's Fashions'), diacritic-insensitive matching, and accepted country codes. It does not specify return format or empty-result behavior, but for a read-only listing tool these are minor gaps.

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

Conciseness4/5

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

The description is well-structured: a one-sentence summary, a compact behavior note, and a terse Args list. Every sentence adds information; the Args section is useful precisely because the schema lacks descriptions. The only minor redundancy is repeating default values already in the schema.

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?

Given three simple parameters, no annotations, and no output schema, the description covers purpose, filtering behavior, parameter constraints, and match quirks well. It omits when to choose this over sibling tools and the shape of returned store objects, but the core calling contract is clear.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must supply all parameter meaning. It does, with examples for category ('Fashion', 'Food Court'), allowed country values (ro, us, gb, hu), and a max_results range (1-100) that supplements the schema's default. This fully compensates for the bare 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 opening sentence 'List stores by category, optionally filtered by country' uses a specific verb and resource, and the matching semantics are clearly described. It differentiates by the category dimension but never explicitly contrasts with siblings like search_stores or stores_by_city, which could also involve category filtering.

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?

The description conveys useful context about when matching works, such as multilingual, hierarchical, and diacritic-insensitive substring matching, which implies use for fuzzy category lookups. However, there is no explicit guidance on when to prefer this tool over search_stores or stores_by_city, nor any when-not-to-use conditions.

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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