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

Annotations already declare this is a read-only, non-destructive, closed-world operation, and the description adds useful behavioral context: it lists all classifications and returns bilingual names and IDs. It does not describe ordering or pagination, but those are minor for a small static reference list.

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 definition is two tight sentences with no wasted wording. Scope and return content are front-loaded, so an agent can parse the essential information immediately.

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 zero-parameter, read-only reference-list tool with no output schema, the description is complete enough: it states the domain, what is listed, and what is returned. No additional behavioral or parameter detail is needed to invoke it correctly.

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?

The tool has zero parameters, so there are no parameter semantics to explain. The description appropriately focuses on scope and return content instead, matching the baseline for a no-parameter tool.

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 a specific verb and resource: list all industry classifications used in EDINET for Japanese listed companies. It clearly describes what the tool returns, but it does not explicitly contrast itself with sibling tools such as get_industry_overview or screen_companies.

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 phrase 'for use in company filtering' gives clear context for when to use the tool. However, it does not name alternative tools or explicitly state when not to use it, leaving sibling routing to inference.

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