Merchgraph (Kingdom Hearts)

Explain product

explain_product

Returns product details such as line, character, dimensions, resale history, and source URLs from a SKU ID or natural-language query, helping users resolve merchandise information.

Instructions

sku_id または自然文クエリから、商品ライン・キャラ・寸法・再販履歴・出典URLなど商品の詳細を返す。

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "explain_product"
  }
}

Input Schema

Name	Required	Description	Default
`query`	No	自然文クエリ（sku_id が無い場合に使用）
`sku_id`	No	正規SKU_ID（sku_id か query のどちらか必須）

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.1Oct 23, 2026

TDQS

B3.1/5.0

Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits itself. It reveals the kinds of data returned, but says nothing about read-only/non-destructive behavior, authentication, rate limits, error handling, or what happens when a query is ambiguous or when neither identifier is supplied.

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, front-loaded sentence with no filler; it states the input modes first and then the returned information, which is exactly the structure an agent needs.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple two-parameter lookup with no output schema, the description usefully enumerates the returned fields (product line, character, dimensions, resale history, source URL). However, it lacks the when-to-use routing and behavioral disclosure needed without annotations, leaving material gaps for an agent choosing among six sibling tools.

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%, and the schema already explains that sku_id and query are alternatives and that query is natural-language. The description repeats the either/or input modes but adds no syntax, format, or validation detail beyond the schema, so the baseline 3 applies.

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 (返す, 'returns') and enumerates the resource details returned (product line, character, dimensions, resale history, source URL), which distinguishes it from generic listing tools. It does not explicitly name or contrast with siblings such as resolve_listing, so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description only notes that either a sku_id or a natural-language query may be supplied; it gives no guidance on when to choose this tool over resolve_listing, discover, or resolve_listings_batch, and no exclusions or prerequisites. Usage is implied at best through the purpose statement.

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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