furigana_classify

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

The description adds output details (probability and character-type breakdown) beyond the readOnlyHint annotation. It does not contradict annotations and provides useful behavioral context about what the result contains.

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 that covers the verb, resource, categories, and output components without redundancy.

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 one-parameter tool with no output schema, the description adequately covers the return values (probability and character-type breakdown) and classification categories. It could be more explicit about the breakdown's composition but is sufficiently complete.

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 input schema already fully describes the 'text' parameter, and the description's phrase 'Japanese string' is synonymous with the schema's 'Japanese text to classify.' No additional parameter semantics are provided.

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 uses the specific verb 'classify' with the resource 'Japanese string' and enumerates the classification categories and output components, clearly distinguishing it from sibling tools like furigana_convert or furigana_name_readings.

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 does not explicitly indicate when to use this tool over the sibling furigana tools; however, the 'classify' verb and the listed categories imply its purpose for type classification. No exclusions or alternative guidance is provided.

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