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moma1992

Yaizu Smart City MCP Server

by moma1992

generate_api_command

Generate API commands for Yaizu City's smart city data by specifying entity types like Aed or EvacuationShelter, using API catalog information to propose appropriate parameters.

Instructions

指定したエンティティタイプに対するAPI実行コマンドを生成します。 APIカタログの情報を基に適切なパラメータを提案します。

Args: entity_type: エンティティタイプ(例: Aed, EvacuationShelter)

Returns: str: 使用可能なAPIコマンド例

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entity_typeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool generates API commands but doesn't specify whether this is a read-only operation, whether it requires authentication, what happens if the entity_type is invalid, or any rate limits. The description is functional but lacks important behavioral context.

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 efficiently structured with a clear purpose statement followed by Args and Returns sections. Every sentence earns its place, and the information is front-loaded with no wasted words. The bilingual format (Japanese description with English Args/Returns) is compact.

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 single-parameter tool with an output schema (which handles return value documentation), the description is minimally adequate. However, given the sibling tools and lack of annotations, it should provide more context about when this generation is useful versus directly executing or getting API details.

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

Parameters4/5

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

With only 1 parameter and 0% schema description coverage, the description compensates well by explaining what entity_type represents ('entity type' with examples like 'Aed, EvacuationShelter') and clarifying that it's used to generate appropriate API commands based on API catalog information. This adds meaningful context beyond 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 description clearly states the tool's purpose: 'generate API execution commands for specified entity types' and 'proposes appropriate parameters based on API catalog information'. It specifies the verb (generate) and resource (API commands), but doesn't explicitly differentiate from sibling tools like execute_api_endpoint or get_api_details.

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 provides no guidance on when to use this tool versus alternatives like execute_api_endpoint (which likely executes commands) or get_api_details (which likely provides API information). There's no mention of prerequisites, use cases, or exclusions.

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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