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 usefully discloses the datasets, years, and statistical sources behind the returned values, but it does not state that this is a read-only lookup, how errors or unknown industries are handled, or how results are structured.

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 a single, front-loaded sentence beginning with the resource and then enumerating the included metrics. It is dense but every clause adds data-scope information; the parenthetical source citations are somewhat heavy but not wasteful.

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?

With one parameter, no output schema, and no annotations, the description should clarify return structure and usage boundaries. It adequately inventories the kinds of data returned but leaves unclear whether the response covers one queried industry or all industries, and how the metrics are organized.

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 100%, and the single query parameter is already documented with examples in the schema. The description does not mention the query parameter or add syntax or format details beyond what the schema provides, so baseline 3 is appropriate.

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 specifies the resource (industry-level statistics) and enumerates the concrete metrics returned: job-opening ratios, wages, prefecture comparisons, and company-size financial metrics with sources/years. It is clear what data the tool retrieves, but it does not explicitly distinguish itself from the sibling list_industries or job_openings.

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?

There is no explicit when-to-use or when-not-to-use guidance. The description never says to use list_industries first to find valid industry names, nor how this differs from job_openings, which appears to overlap with the job-opening-ratio data.

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