japan-ux-mcp

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 discloses key behavioral traits: the tool generates markup with specific cultural features (e.g., field order, furigana, phone format) and adapts keigo based on context. However, it lacks details on output format (implied but not explicit), error handling, or performance aspects like rate limits. The description adds value but is incomplete for a tool with 7 parameters and no output schema.

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, with the first sentence stating the core purpose and key features, and the second sentence providing usage guidelines. Every sentence earns its place by adding distinct value—no redundancy or waste. It efficiently conveys essential information without unnecessary elaboration.

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 complexity (7 parameters, cultural nuances) and lack of annotations or output schema, the description is reasonably complete. It covers the purpose, key features, and usage context, but could benefit from more behavioral details (e.g., output format clarification, error handling). However, it adequately supports agent understanding for a generation tool with well-documented parameters 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?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds marginal semantic context by implying how 'context' affects keigo level and 'fields' includes culturally appropriate elements, but it doesn't provide additional syntax or format details beyond what the schema specifies. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't significantly enhance parameter understanding.

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 specific action ('generate culturally correct Japanese form markup') and resource ('Japanese form'), listing key features like field order, furigana, phone format, postal address, dates, and keigo. It explicitly distinguishes this tool from siblings by specifying 'when building any form for a Japanese audience,' which contrasts with tools like 'validate_jp_form' or 'suggest_keigo_level' that serve different purposes.

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 guidance on when to use this tool: 'Use this when building any form for a Japanese audience.' This clearly defines the primary use case and context, helping the agent distinguish it from alternatives like 'generate_jp_placeholder' (likely for placeholder text) or 'transform_for_japan' (likely for conversion tasks). No exclusions are stated, but the positive guidance is sufficient for high clarity.

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