japan-ux-mcp

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the output format in detail (e.g., 'kanji + katakana furigana + romaji', 'real postal codes and prefectures'), which is valuable, but does not cover aspects like rate limits, error handling, or data sources. It adequately informs that the tool generates data but lacks deeper behavioral traits.

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 appropriately sized and front-loaded, starting with the core purpose and efficiently listing output types in a single, well-structured sentence. Every phrase adds value without redundancy, making it easy for an agent to quickly grasp the tool's function.

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?

Given the tool's moderate complexity (4 parameters, no output schema, no annotations), the description is largely complete. It details the output format comprehensively, which compensates for the lack of output schema. However, it could improve by mentioning constraints like the 'count' maximum or 'fields' enum options, though these are covered in the schema.

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 has 100% description coverage, providing clear details for all parameters (e.g., 'count', 'fields', 'gender', 'age_range'). The description adds minimal value beyond the schema by mentioning 'Japanese era format' for dates, which relates to output rather than input. Baseline score of 3 is appropriate as the schema does the heavy lifting.

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 the tool's purpose with specific verbs ('Generate realistic Japanese test data') and resources ('names, addresses, phone numbers, company names, and dates'), distinguishing it from siblings like 'validate_jp_form' or 'transform_for_japan' by focusing on data generation rather than validation or transformation.

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 context ('for prototypes and development') but does not explicitly state when to use this tool versus alternatives like 'generate_jp_form' or 'suggest_keigo_level'. It lacks guidance on exclusions or prerequisites, leaving the agent to infer appropriate scenarios.

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