japan-seasons-mcp

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

Annotations already declare readOnlyHint=true and idempotentHint=true, indicating safe, repeatable operations. The description adds valuable context: it specifies the data source (Japan Meteorological Corporation), the return format (dates, leaf type, rating, coordinates), and the fallback behavior when prefecture is omitted. It doesn't contradict annotations, but could mention rate limits or authentication needs if applicable.

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 efficiently structured in three sentences: first states the core use case and return data, second explains the omission behavior, third provides explicit exclusion guidance. Every sentence adds value with no redundancy, and it's front-loaded with the primary purpose.

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 has one optional parameter with full schema coverage and annotations covering safety/idempotency, the description is largely complete. It explains the tool's behavior with and without the parameter, distinguishes from siblings, and specifies the return data. However, without an output schema, it could more explicitly detail the response structure (e.g., list format, pagination).

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 fully documents the single optional parameter. The description adds semantic context: it explains that omitting prefecture returns a 'top-destinations guide' across Japan, which clarifies the tool's dual functionality beyond what the schema states. However, it doesn't provide additional details on parameter format or constraints.

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: it returns Japan Meteorological Corporation koyo spots for one prefecture with specific data fields (best start/peak/end dates, leaf type, popularity rating, GPS coordinates). It distinguishes from siblings by specifying it's for 'autumn leaves viewing spots' and contrasts with tools like koyo_forecast or koyo_best_dates for cross-city date matching.

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: 'Use this when the user already knows the prefecture and needs exact autumn leaves viewing spots.' It also specifies when not to use it ('Do not use this for cross-city date matching; use koyo_forecast or koyo_best_dates first') and mentions an alternative behavior when prefecture is omitted ('Omit prefecture to get a top-destinations guide').

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