get_api_spec

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

With no annotations provided, the description carries the behavioral disclosure burden and does it well: it explains that the tool returns full parameter constraints, fetches one real data record for preview, and generates parameter hints from actual data. It does not discuss error conditions, permissions, or rate-limit effects of the data preview, but the core read behavior is transparent.

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 with '기능', '워크플로우', 'Args', and 'Returns' sections, making it easy to scan. The main purpose is front-loaded, and the workflow and feature details are directly actionable with little redundancy.

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 one required parameter, an output schema, and no annotations, the description supplies all essential invocation context: parameter semantics with an example, return summary, and an explicit workflow connecting sibling tools. Missing edge-case details are not critical for this read-oriented lookup tool.

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 only says service_id is a required string with 0% schema description coverage. The description compensates by labeling it as the service ID and giving a concrete example ('O4K6HM0012064I15889'). It does not provide format rules or constraints beyond the example, but for a single parameter this is sufficient.

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 opens with '특정 API 서비스의 상세 스펙을 조회합니다', naming a specific verb and resource, then lists endpoint URL, request parameters, and response structure. It also distinguishes itself from high-level tools by saying it is useful when dynamically exploring API details that high-level tools do not provide, which separates it from siblings like list_api_services and call_api_raw.

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?

An explicit three-step workflow is provided: use list_api_services to find the service ID, call this tool for parameter details, then use call_api_raw. It also states that it is useful for dynamic API exploration. It does not spell out an explicit 'when not to use' condition, but the workflow gives strong contextual guidance.

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