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

No annotations are provided, so the description carries the full burden. It states that the tool returns 'the original meaning and how to wash at home', which describes the primary behavior. However, it does not disclose what happens for unrecognized inputs, error cases, or limitations such as requiring internet access. This is a moderate gap for a lookup tool without annotations.

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, well-structured paragraph that front-loads the purpose, provides concrete examples, references a supplementary API, and gives usage scenarios. Every sentence earns its place, and there is no fluff or redundancy. The flow is logical and easy to parse.

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 tool with a single required parameter and no output schema, the description is quite complete. It includes examples, usage guidance, a reference to a full list, and the screen path. It doesn't specify the exact return format, but that is not necessary given the simplicity. The only minor omission is error handling or fallback behavior, but overall it is sufficient for an agent to invoke 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?

Schema coverage is 100% for the q parameter, with examples provided in the schema. The description adds further value by explaining the expected phrasing style (e.g., '丸にバツ') and giving multiple examples, clarifying the format beyond the schema. It also indicates that the parameter accepts colloquial descriptions, which enhances usability.

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 states a specific verb and resource: it explains laundry symbols (洗濯表示) and returns meanings and washing instructions from JIS L 0001:2024. It gives concrete examples of query phrases and distinguishes its purpose from unrelated siblings. The phrase 'このマークは何' etc. further clarifies the domain.

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 provides explicit usage scenarios: for consultations like 'what is this mark', 'can I put it in the dryer', 'can I wash it at home'. It also mentions a full list endpoint, guiding users who need the complete set. It doesn't explicitly name alternatives, but given the unrelated sibling set, the context is sufficient.

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