get_daily_mean_temperature

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the function without mentioning units, data source, filtering behavior, error handling, or response format. There is no indication of whether this returns historical data or current data, or what happens if no data matches the station/year/month.

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 a single, clear sentence with no wasted words. It is front-loaded and easily digestible. The structure could be improved by adding more detail, but for what it contains, it is concise and well-formed.

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?

The tool has an output schema that covers return values, but the description still lacks essential context about optional filters (year, month) and the meaning of 'daily' in terms of time range. The description does not mention that the user can specify a particular year/month, despite these being available in the schema. This makes the description incomplete for proper invocation in many realistic scenarios.

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 0%, so the description must compensate. It only mentions 'specific station,' which aligns with the required 'station' parameter. However, it does not explain the optional 'year', 'month', or 'lang' parameters, nor does it clarify their formats or the effect of omitting them. This leaves the agent to infer most parameter semantics from names alone.

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 identifies the tool as retrieving daily mean temperature data for a specific Hong Kong station. The verb 'get' and resource 'daily mean temperature data' are specific, and the word 'mean' distinguishes it from sibling tools like get_daily_max_temperature and get_daily_min_temperature.

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 says to use this for daily mean temperature, which implies a retrieval scenario. However, it does not explicitly state when to choose this over alternatives or when not to use it. No exclusions or comparisons are provided, though the tool's name and description make the primary use case obvious.

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