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 of behavioral disclosure. It mentions the tool 'suggests' and 'returns' translations, implying a read-only operation, but does not clarify if it requires authentication, has rate limits, or details the return format (e.g., structured output). For a tool with no annotations, this leaves significant gaps in understanding its behavior.

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 with two sentences that are front-loaded with the core purpose. It efficiently lists UI elements and contexts without redundancy, though the second sentence could be slightly more streamlined by integrating the examples more cohesively.

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 complexity of language translation and cultural adaptation, the description is moderately complete. It lacks an output schema, so the agent does not know the return format (e.g., whether it includes multiple translations or keigo levels). With no annotations and incomplete behavioral details, it provides a basic understanding but leaves gaps for effective tool invocation.

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 minimal value beyond the schema by mentioning 'maps business context to keigo level' and listing examples like 'buttons, error messages,' which loosely correlate with the ui_element enum. However, it does not provide additional syntax or format details, aligning with the baseline score when schema coverage is high.

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: 'Suggest appropriately polite Japanese UI text based on context.' It specifies the verb ('suggest'), resource ('Japanese UI text'), and scope ('based on context'), distinguishing it from sibling tools like generate_jp_form or validate_jp_form. The mention of mapping business context to keigo levels and returning translations for specific UI elements adds specificity.

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 by mentioning 'based on context' and listing UI elements and business contexts, but it does not explicitly state when to use this tool versus alternatives like generate_jp_form or transform_for_japan. No exclusions or prerequisites are provided, leaving the agent to infer appropriate contexts from the parameter enums.

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