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

Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false), but the description adds genuine behavioral traits: responses are trimmed to ~20KB, columns capped at 50, version_keys limited to the latest 3, and a truncated field reports what was cut. This is real context an agent needs to interpret partial results.

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?

Purpose is front-loaded and useful, but the same content is duplicated in Korean and English, roughly doubling length, and the return-field enumeration is largely redundant with the existing output schema. Adequate but not tight.

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?

Since an output schema exists, enumerating return fields is not strictly required, yet the description still supplies the operation-selection workflow, the 20KB truncation caveat, and the get_preview handoff. An agent has enough to call it correctly; only minor edge cases (e.g. behavior when truncated) are left implicit.

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 description coverage is 0%, so the description must carry the load. It explains the operation parameter concretely with syntax ('show(id, operation=\'기능명 또는 operation_seq\')'), clarifying it accepts either a name or a sequence. dataset_id is only implicitly covered, which keeps this from a 5.

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?

States a specific verb and resource in both Korean and English: inspect a dataset's schema and access methods ('데이터셋의 구조와 접근 방법을 봅니다'). An agent can immediately distinguish this from search (discovery), get_preview (row data), fields, and record.

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?

Gives a clear selection context ('검색에서 고른 데이터셋' – a dataset picked from search) and routes to a sibling: use get_preview to check the actual first row. It also explains the when-to-use for the operation parameter (when an API has many operations). It lacks an explicit 'when not to use', so not quite a 5.

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