japan-seasons-mcp

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

The annotations declare readOnlyHint=true and idempotentHint=true, indicating safe, repeatable operations. The description adds valuable behavioral context beyond annotations: it explains that month filtering automatically narrows results to fruits in season during that month, and that results come from a 'local dataset.' However, it doesn't mention rate limits, authentication needs, or pagination 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 perfectly structured and concise with just two sentences. The first sentence front-loads the core purpose and key features. The second sentence provides crucial usage guidance without redundancy. Every word earns its place with zero wasted text.

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 read-only, idempotent query tool with excellent schema coverage, the description provides strong contextual completeness. It explains the tool's purpose, usage guidelines, and key behavioral aspects. The main gap is the lack of output schema, leaving return format unspecified, but the description mentions what information is returned (farms, booking links, map coordinates).

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?

With 100% schema description coverage, the input schema already thoroughly documents all four parameters. The description adds minimal parameter semantics beyond the schema, only mentioning that month filtering 'automatically narrows results to fruits that are in season' and that results come from a 'local dataset.' This meets the baseline expectation when schema coverage is complete.

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: retrieving fruit-picking farms with booking links and map coordinates from a local dataset. It specifies the exact resources (farms) and functionality (filtering by season via month parameter), distinguishing it from sibling tools like 'fruit_seasons' which only provides seasonal information without farm details.

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 versus alternatives. It states to use this tool when users need actual farms with booking links and coordinates, and specifically instructs to call 'fruit_seasons' first if the user only asks about fruit seasons, creating a clear decision flow between sibling tools.

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