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

With no annotations, the description carries the disclosure burden and does well: it names the data source (JMA observations), the historical start (1991), the 40 km station-proximity rule, and the output granularity implied by each parameter combination. It omits failure behavior when no station falls within 40 km and any rate/auth constraints.

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?

Resource and constraints are front-loaded in the first clause, followed by the combination rules. It is dense but nearly every clause carries operational information; only the closing 'not a forecast' restates a point already implied by '過去'.

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 3-parameter read tool with no annotations and no output schema, the definition covers source, time range, spatial constraint, and granularity rules well. The remaining gap is the return shape (units, which metrics come back per row), which the agent must infer.

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 coverage is 100%, so the baseline is 3; the description earns above that by explaining the interaction of year and month — the semantics of each combination is nowhere in the schema, which only labels them '年' and '月'. The station parameter meaning is largely repeated from the schema rather than extended.

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?

States a specific retrieval (past monthly average temperature, wind speed, precipitation) tied to a named, constrained resource (nearest JMA station within 40 km of the port, data from 1991 onward). It explicitly distinguishes itself from forecast-style tools with '過去の観測で、予報ではない', so an agent can tell what it is and is not without opening the schema.

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?

Gives an exhaustive mapping of when each invocation shape applies: year only → 12 months of that year, month only → that month across years, both → a single month, neither → latest 12 months. That is strong usage context, but it never names a sibling tool or an exclusion condition (e.g. use get_tide instead for tide data), so it falls short of a 5.

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