Skip to main content
Glama

エキテン ネット予約

get_genres

エキテンの大ジャンル・小ジャンルの全件一覧を取得する。ジャンルはキーワード検索ではなく一覧から選ぶ方式。引数は不要。AIはユーザーの入力(「美容」「グルメ」等)とレスポンス内の largeGenreName / smallGenreName を照合し、該当する largeGenreId / smallGenreId を選択すること。曖昧または複数該当する場合はユーザーに確認すること。取得したIDを店舗検索ツールに渡す。【次のステップ】選択した largeGenreId / smallGenreId を使って search_shops を呼び出す。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations present, the description carries the full burden. It discloses that the tool takes no arguments, returns genre names and IDs, and requires the AI to perform matching and confirmation. No hidden side effects or permissions are implied, and the behavior is fully transparent.

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 slightly verbose, repeating the matching instruction and the next-step guidance, but each sentence carries essential operational detail. It could be tightened without losing clarity, yet it remains well-structured and readable.

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

Completeness5/5

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

Given the absence of an output schema, the description adequately specifies the response elements (largeGenreName/smallGenreName, largeGenreId/smallGenreId) and the decision logic for handling ambiguous matches. It also explains the follow-up action, making the tool's context fully understandable.

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?

Although the schema has zero parameters, the description explicitly states '引数は不要' (no arguments required), which confirms the parameter expectation and prevents any misinterpretation. This adds clarity beyond the empty schema, though the baseline for zero parameters is already 4.

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 clearly states the tool retrieves the full list of major and sub genres ('大ジャンル・小ジャンルの全件一覧を取得する') and explicitly distinguishes its purpose from keyword search, positioning it as a selection-from-list mechanism. It also indicates the subsequent use of the retrieved IDs, leaving no ambiguity about the tool's role.

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

Usage Guidelines5/5

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

The description provides explicit when-to-use guidance: it instructs the AI to match user input (e.g., '美容', 'グルメ') against genre names and select the corresponding IDs, and specifies to ask for confirmation if ambiguous or multiple matches. It also names the next step (call search_shops with the selected IDs), effectively guiding the agent through the workflow.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.3/5.0
Disambiguation5/5

Each tool has a unique, clearly defined purpose: login, logout, search, genres, availability, create, and cancel. No two tools overlap in functionality, making selection straightforward.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern in snake_case (e.g., search_shops, get_availability, create_reservation). This predictable naming makes the API easy to navigate.

Tool Count5/5

Seven tools neatly cover the necessary operations for an online reservation system without redundancy or bloat. The scope is appropriately focused on the core workflow.

Completeness4/5

The toolkit covers the essential reservation lifecycle: login, search, availability check, create, cancel, and logout. While an update/modify reservation tool is absent, it is not a typical requirement for this type of system, so the coverage is nearly complete.

Resources