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

No annotations are provided, so the description must carry the behavioral burden. It discloses useful dataset context such as sample sizes and the metrics returned, but it does not describe return format, pagination, or other operational traits an agent might need.

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 compact and front-loaded, stating the dataset scope first, then filtering and sorting behavior. Every sentence contributes useful information without repetition.

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?

For a two-parameter read-only data exploration tool with no annotations or output schema, the description supplies enough context about the dataset, metrics, filtering, and sorting to select and call it correctly. The main missing piece is explicit differentiation from the sibling risk_overview tool.

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 100%, but the description still adds meaningful semantics: query filters by part of a category name, and sort_by values are explained as JP rank, US rank, and largest rank gap. This goes beyond simply repeating enum labels.

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 clearly identifies the resource: 31 categories of business risks reported by 3,766 Japanese and 3,808 US listed companies, including Japan/US rankings, proportions, and rank gaps. It is specific about scope and metrics, but it does not explicitly distinguish this tool from the sibling risk_overview tool.

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 implies usage by explaining that query can narrow categories by name and sort_by controls ordering. However, it does not state when to use this tool instead of alternatives such as risk_overview, nor does it provide exclusions or prerequisites.

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