list_api_services

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

With no annotations, the description carries the behavioral disclosure burden. It clearly signals a read-only search operation, states the matching scope (service name or description), and describes the return items as containing id, name, and description. It does not mention default-keyword behavior or pagination, but the operation is a simple search and the description is sufficiently 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 compact and well-structured: a one-line summary, a short actionable workflow list, then Args/Returns. Every sentence adds useful information, with no filler or repetition of schema details.

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?

For a simple one-parameter discovery tool, the description provides enough context: what it searches, how to use the results, and what the return items contain. The presence of an output schema reduces the need to detail return structure. A minor gap is the unspecified behavior when keyword is empty/default, but overall the tool is adequately contextualized.

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?

Schema coverage is 0%, but the description fully compensates by explaining the keyword parameter: 'Keyword to search in service name or description.' It also enriches usage by advising broad keyword attempts, including Korean/English and partial substring matching. With a single parameter, this is complete semantic coverage.

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 a specific verb and resource: '모든 OpenAPI(총 270여 개) 메타데이터를 검색합니다' (searches metadata for all ~270 OpenAPIs). It also differentiates this tool from high-level tools by framing it as the low-level fallback for finding service IDs, making its purpose unmistakable.

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 explicit guidance on when to use it: '고수준 툴에 없다고 끝내지 말고, 여기서 서비스 ID를 찾은 뒤 get_api_spec → call_api_raw로 직접 호출하세요.' This states the condition, the action, and the follow-up workflow. It also adds practical search strategy by telling the agent to try Korean/English, spacing variants, and partial substrings.

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