get_daily_max_temperature

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

With no annotations, the description carries the full burden of behavioral disclosure. It merely restates the purpose without explaining how optional parameters (year, month) affect results, what station identifiers are valid, or any historical data range constraints. The description adds no behavioral context beyond the basic 'get data' intent.

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, front-loaded with the action and resource. It is concise and easy to parse, though it could include more useful context without becoming bloated.

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?

Despite having an output schema, the description omits critical context such as optional parameter semantics (year/month default to null), the relationship to sibling temperature tools, and any special behavior. For a simple data retrieval tool with four parameters, the description is too sparse for an agent to invoke it effectively in varying 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, but it only mentions 'specific station,' aligning with the required 'station' parameter. It does not clarify the meaning or default behavior of 'year', 'month', or 'lang', leaving the agent with incomplete information for constructing calls.

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 uses a specific verb ('Get') and identifies the exact resource ('daily maximum temperature data') with a clear geographic scope ('for a specific station in Hong Kong'). This distinguishes it from sibling tools like get_daily_mean_temperature and get_daily_min_temperature, which share the same station/city context but target different metrics.

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 no guidance on when to use this tool versus the sibling temperature tools (mean/min) or other weather data tools. It implies usage via the metric name but does not state prerequisites, filtering scenarios, or alternatives.

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