get_maintenance_equipment

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

No annotations are provided, so the description carries the full burden. It discloses the data as-of date (2024.12.31), the 16-region scope, and the default behavior (returns all regions if region is empty). It also hints at the granularity of data by listing the machine categories. It does not explicitly state read-only behavior, but the verb '조회' (inquiry) strongly implies a non-mutating operation, and there is no mention of side effects. The lack of explicit mutability note is minor given the query nature.

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

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

The description is well-structured: it opens with the main purpose, then details the parameter semantics, and ends with the default behavior. The list of machine categories is lengthy but provides useful detail about the data scope. It is somewhat verbose for a simple tool, but every part contributes informational value, and the structure facilitates quick scanning.

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

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

Given the tool's simplicity (one optional parameter) and that an output schema exists, the description covers the essential points: what the tool returns, how to filter, and the default behavior. It does not explain output structure, but that is provided by the output schema. Any missing edge cases (e.g., no matches) are not addressed, but for a query tool of this nature the description is sufficiently complete.

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

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

The input schema provides only a string with a default; there is no schema description (0% coverage). The tool description compensates thoroughly by explaining that 'region' supports partial matching, gives concrete examples ('수도권', '부산', '대전', '강원'), clarifies that it can be filtered by '정비단' or '지역본부', and states the outcome when left empty. This goes well beyond the schema and leaves no ambiguity about the parameter's meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action (조회/inquiry), the resource (철도차량 검수용 기계 보유현황, railway vehicle inspection machine inventory), and even the as-of date and scope (16 regions). It distinguishes itself from sibling tools by focusing specifically on maintenance equipment, not on stations, routes, or customer data. An agent can immediately understand what this tool returns.

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

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

The description gives clear usage guidance for the parameter: partial matching, examples, how to filter by 정비단 or 지역본부, and the default behavior when no input is provided. It does not explicitly mention alternative tools, but among the siblings there is no obvious competitor, so the lack of an explicit alternative is not a significant omission. The guidance is practical and sufficient for correct invocation.

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