enumerate

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

With no annotations, the description carries the full behavioral burden and does so thoroughly: it states determinism, that the response is a complete member list from an authoritative curated taxonomy, that definitions are pulled from the graph, that gaps honestly signal missing graph data, and that the agent must not fabricate content. It even discloses the fallback behavior for non-curated topics.

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 yet information-dense: purpose, examples, sibling routing, fallback, and honesty guarantees all appear in a few sentences. Core intent is front-loaded before caveats, and no sentence is redundant with the schema or output schema.

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 one-parameter tool with an output schema and no annotations, the description covers everything needed: what it returns, how it behaves, when to call it, how to distinguish it from siblings, fallback behavior, and how to interpret gaps. There are no material gaps that would prevent correct invocation.

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 100% for the single query parameter, so the baseline is 3. The description adds value beyond the schema by defining the accepted query pattern ('X의 종류/체계/구성요소') and clarifying the match=None case that affects behavior, which helps the agent form valid inputs.

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 names a precise verb-and-resource combo: completely enumerate the kinds/components/classifications of an entity, with concrete examples like '건축물 하중의 종류'. It also differentiates itself from siblings by explicitly routing ordering to scenario and comparison to compare, so the agent can select it correctly.

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 when-to-use criteria ('X의 종류/체계' requests), names alternatives for other request types (scenario, compare), and specifies the fallback to k_snippets when match=None. This is clear routing guidance rather than leaving usage to inference.

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