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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds genuinely new behavioral context: the fixed three-year lookback window, the default top-5-partner aggregation versus single-country restriction, and the derived metrics returned (yoy range, peak/low months). It stops short of explaining the min_value filtering effect on which partners appear, or any truncation 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 English sentence is front-loaded and dense with the key facts — scope, metrics, and aggregation default — with no filler. The full Japanese restatement doubles the length, which is defensible for a bilingual server but is still redundant text for a single agent.

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?

With no output schema, the description carries the burden of describing return values and does so concretely (monthly shares, yoy range, peak/low months, partner breakdown). Combined with the fully documented six-parameter schema, an agent has enough to call this correctly and interpret the result without further guessing.

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 baseline is 3, and the description earns a bump by clarifying the aggregation default that the schema does not encode: without `country` the result aggregates the world plus the top 5 partners, while supplying `country` returns just that country. That is real added meaning beyond the property descriptions.

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 names a specific resource (seasonality) and spells out exactly what it computes: monthly shares over the last three full years, the year-to-year range, peak and low months, for the world and the top 5 partners or a single country. This is clearly distinguishable from siblings like get_series and get_partners, which return raw series or partner lists rather than a derived seasonality profile.

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?

It implies when the tool is appropriate by describing the shape of the answer (three-year monthly shares, peak/trough) and notes that passing `country` narrows to one country instead of the default top-5 set. However, it never states when to prefer this over get_series or get_item_summary, nor does it mention prerequisites or exclusions, leaving the routing decision to inference.

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