get_stats_data

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions that the tool 'gets' data (implying read-only), but doesn't address authentication requirements, rate limits, error conditions, or what happens when parameters are omitted. The description provides minimal behavioral context beyond the basic operation.

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 structured with a brief purpose statement followed by organized parameter documentation. However, the initial purpose statement is overly brief and uninformative. The parameter documentation is comprehensive but could be more efficiently organized, especially for the repetitive lvcat parameters. The structure is adequate but not optimal.

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 the tool's complexity (25 parameters, no annotations, but has output schema), the description provides good parameter documentation but lacks critical context about usage guidelines, behavioral traits, and differentiation from sibling tools. The presence of an output schema means the description doesn't need to explain return values, but other gaps remain significant for a tool of this complexity.

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 and 25 parameters, the description provides substantial parameter documentation in Japanese, explaining each parameter's purpose (e.g., '統計表ID', '絞り込み用' for filtering, 'データ取得開始位置', default values). This compensates well for the complete lack of schema descriptions, though some parameters like the lvcat series could use more explanation about their hierarchical relationships.

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 '統計データを取得する' (get statistical data), which is a tautology that essentially restates the tool name 'get_stats_data'. It doesn't specify what kind of statistical data, from what source, or how it differs from sibling tools like 'get_stats_data_bulk' or 'get_stats_data_csv'. The purpose is vague and doesn't provide meaningful differentiation.

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 about when to use this tool versus alternatives. With multiple sibling tools available (get_stats_data_bulk, get_stats_data_csv, get_stats_list, etc.), the description offers no context about when this specific retrieval method is appropriate versus bulk operations, CSV exports, or other statistical data tools. The agent receives no usage context.

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