compare_regions

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

With no annotations, the description carries full behavioral burden. It discloses the return format (Markdown pivot table), the structural orientation (years as rows, regions as columns), and the filtering behavior of optional codes. It stops short of discussing error handling or area resolution, but for a read-style data retrieval tool this is solid coverage.

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 front-loaded with the core purpose, immediately followed by the pivot-table structure, then an Args list and Returns line. Every sentence serves a functional role; there is no filler or redundant restatement of the tool name.

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?

All required parameters are explained with examples, and the return format is specified. The description could optionally mention how to discover tab_code/cat01_code values (e.g., via get_meta_info), but that is a minor gap given these are optional and an agent can infer the workflow from sibling tools.

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 0%, so the description is the sole source of parameter meaning. Each parameter gets a purpose: stats_data_id is sourced from search_statistics, areas includes a concrete example list, tab_code is for filtering by indicator, and cat01_code is for filtering by category. This adds substantial meaning beyond bare titles and types.

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 opens with a clear verb and object: '複数地域の統計データを比較する' (compare statistical data across multiple regions), and specifies the output artifact: a pivot table with time as rows and regions as columns. This distinguishes it from sibling tools focused on single-region data (get_regional_data, get_population) or metadata lookup (get_meta_info).

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 clearly frames the tool's context: comparing multiple regions' statistics. It also provides a prerequisite: stats_data_id is obtained via search_statistics. It does not explicitly name alternatives or exclusions, but the intended use case is clear enough for an agent to select it over get_regional_data or get_regional_profile.

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