japan-seasons-mcp

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

Annotations indicate read-only and idempotent operations, which the description doesn't contradict. The description adds valuable behavioral context: it specifies the scope (14 fruits, includes peak months, regions, notes), mentions the optional month parameter's effect (returns fruits in season plus those starting next month), and guides next steps (call fruit_farms for related needs). However, it doesn't address potential rate limits or authentication requirements, though annotations cover safety aspects.

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 two sentences: the first states purpose and usage, the second provides guidance on alternatives. Every sentence adds value without redundancy, and it's front-loaded with the core functionality.

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 (1 optional parameter, no output schema), the description is mostly complete. It covers purpose, usage, scope (14 fruits), and next steps. However, it lacks details on output format (e.g., structure of returned data) and doesn't explicitly mention the annotations' read-only/idempotent nature, though annotations handle that. With no output schema, some gaps remain in return value explanation.

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, fully documenting the optional month parameter. The description adds minimal parameter semantics beyond the schema, only implying the month's use for filtering. With high schema coverage, the baseline is 3, and 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 tool's purpose: to return fruit season information (calendar, peak months, best regions, notes) for 14 fruits. It specifies the exact use cases (what fruit is in season in a given month, best month for specific fruits) and distinguishes it from sibling tools by mentioning fruit_farms for farm listings, coordinates, or bookings.

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 explicitly states when to use this tool ('when the user asks what fruit is in season... or which month is best for... picking trips') and provides a clear alternative ('Call fruit_farms next if the user needs actual farm listings...'). It also distinguishes it from other siblings like festivals_list or weather_forecast by focusing on fruit seasons.

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