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

Annotations already declare readOnly/idempotent/non-destructive, so safety is covered. The description adds genuinely useful behavioral context beyond that: responses are trimmed to ~20KB, columns capped at 50, version_keys limited to latest 3, and a 'more' field describes follow-up retrieval. This concisely communicates truncation and drill-down behavior.

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 purpose is front-loaded, which is good, but the long enumerated return-field list is heavy and overlaps with the output schema. It's informative rather than wasteful, yet the bilingual duplication and field catalog make it longer than it needs to be.

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, the return-value enumeration is somewhat redundant, but the description usefully adds the trimming threshold and the operation-drill-down strategy, which the schema cannot express. It is complete enough for an agent to invoke correctly, with only the dataset_id parameter 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 well (accepts a function name or operation_seq to view a single operation's full fields), but says nothing specific about 'dataset_id' format or sourcing. Partial compensation only.

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+resource: inspecting a selected dataset's schema and access methods ('데이터셋의 구조와 접근 방법을 봅니다'). It is clearly differentiable from siblings like search, get_preview, and fields, which handle discovery, row sampling, and field listing respectively.

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?

Explicitly routes the agent: use show(id, operation='...') when an API has many operations, and 'get_preview' to check actual first rows when the dataset looks usable. This gives clear when-to-use context and names alternatives, though it doesn't state when NOT to use this tool.

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