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Alshhbaa Copperware — نحاسيات الشهباء

by io.github.Alshhbaa
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Search Alshhbaa Brassware Products

search_products
Read-only

Search public Alshhbaa Brassware product suggestions without mutating cart or checkout.

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": {
      "query": "<query>"
    },
    "name": "search_products"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum number of product suggestions to return (1-20). Defaults to 5.
queryYesSearch query for chandeliers, chandelier accessories, lamps, and wall sconces (e.g. "ثريا", "chandelier").

Output Schema

NameRequiredDescriptionDefault
contentYes
structuredContentNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / query / description
      Previous value: -"Search query for luxury lighting, chandeliers, lamps, and brass crafts (e.g. \"ثريا\", \"chandelier\")."New value: +"Search query for chandeliers, chandelier accessories, lamps, and wall sconces (e.g. \"ثريا\", \"chandelier\")."
  2. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, and the description mostly restates that guarantee ('without mutating cart or checkout'). It usefully adds that results are 'public' suggestions, but discloses nothing about result ordering, matching behavior, or limits beyond what the schema already says.

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?

A single tight sentence with the action and scope front-loaded and zero filler. Nothing needs trimming.

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?

An output schema exists and annotations cover safety, so the description doesn't need to explain return values. With only two fully documented parameters, the brief description is close to sufficient, though a note on search scope (catalog-wide vs. category-limited) would complete it.

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 description coverage is 100%, so both the query domain (chandeliers, accessories, lamps, wall sconces, Arabic example) and the limit range/default are already documented. The description adds no parameter meaning beyond the schema, which is the baseline case.

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?

States a specific verb (Search) and resource (Alshhbaa Brassware product suggestions) with a scope qualifier ('public'). It is understandable without opening the schema, though it doesn't explicitly differentiate itself from the only sibling, read_docs.

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 phrase 'without mutating cart or checkout' implies a read-only lookup in a shopping context, but there is no explicit when-to-use guidance, no prerequisites, and no mention of alternatives. Usage is inferable rather than stated.

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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