get_dataset

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

No annotations are provided, so the description carries full burden. It mentions that dataset_id is optional (for listing available datasets) and describes pagination with start_position and limit, which adds some behavioral context. However, it lacks critical details like authentication requirements, rate limits, error conditions, or whether this is a read-only operation (implied but not stated).

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 reasonably concise with a purpose statement followed by parameter and return sections. However, the structure mixes Japanese and English inconsistently, and the purpose statement is overly brief. Some sentences could be more informative without adding bulk.

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 no annotations and an output schema (implied by 'Returns'), the description covers basic purpose and parameters adequately. However, for a data retrieval tool with many siblings, it lacks sufficient context about what 'データセット情報' includes versus other tools' outputs, making completeness marginal.

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?

With 0% schema description coverage, the description compensates by explaining all three parameters: dataset_id (optional, for listing when omitted), start_position (data retrieval start position), and limit (number of items to retrieve). This adds meaningful semantics beyond the bare schema, though it could specify data types or constraints more clearly.

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 states 'データセットを参照する' (refer to/view a dataset), which provides a basic verb+resource but is vague about scope and functionality. It doesn't clearly distinguish this tool from sibling tools like 'get_data_catalog' or 'get_meta_info', leaving ambiguity about what specifically this tool retrieves versus others.

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?

No guidance is provided on when to use this tool versus alternatives. With multiple sibling tools for data retrieval (e.g., get_data_catalog, get_meta_info, get_stats_data), the description offers no context on appropriate use cases, prerequisites, or exclusions, leaving the agent to guess based on tool names alone.

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