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 beyond this: it explains the tool's logic (overlap between travel dates and viewing windows) and data sources (observed or forecast full-bloom dates). However, it doesn't detail output format or potential limitations like data freshness or geographic scope.

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 front-loaded with the core purpose in the first sentence, followed by usage guidance and exclusions. Every sentence adds value: the first explains what the tool does, the second clarifies logic and data sources, and the third provides critical exclusion criteria. No wasted words or redundancy.

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 (date-based matching), rich annotations (readOnlyHint, idempotentHint), and full schema coverage, the description is largely complete. It explains purpose, usage, and exclusions well. However, without an output schema, it could benefit from briefly mentioning return format (e.g., list of cities with details), though this is a minor gap.

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%, with both parameters (start_date and end_date) fully documented in the schema. The description adds no additional parameter semantics beyond what the schema provides, such as explaining how date ranges are compared or what 'viewing window' entails. Baseline 3 is appropriate when the schema handles all parameter documentation.

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 identifies cities where cherry blossom viewing windows overlap with the user's travel dates. It uses specific verbs ('returns cities') and resources ('based on observed or forecast full-bloom dates'), and it explicitly distinguishes from sibling tools by mentioning kawazu_forecast for early-bloom requests.

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 ('when the user provides travel dates and wants to know where sakura is likely to be best') and when not to use it ('Do not use this for January-February early-bloom Kawazu requests'), including a named alternative ('use kawazu_forecast for those'). This clearly differentiates it from sibling tools.

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