get_historical_weather

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

With no annotations, the description carries the disclosure burden. It reveals the 80+ year data archive, the effect of include_hourly, date-range inputs, and the shape of the response. It does not mention API limits or the fact that it does not return current conditions, but it is substantially transparent for a read-only historical query tool.

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 well-structured with a clear first sentence, a supporting '80+ years' fact, use cases, examples, Args, and Returns sections. It is longer than minimal, but the length is justified given zero schema descriptions and six parameters to document.

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?

All required parameters are identifiable, optional behavior is described, and the return structure is outlined. The description gives enough context an agent needs to decide and call the tool correctly, though it could mention maximum date range or timezone semantics explicitly.

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 Args section is essential. It documents all six parameters, including decimal-degree latitude/longitude, ISO date format, defaults for include_hourly and timezone, although it could have provided more detail like date-range constraints.

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 clear verb and resource: 'Retrieves historical weather data' for trend analysis. The word 'historical' differentiates it from current-weather siblings like get_weather, and the use cases and examples reinforce the intended scope.

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?

Provides explicit use cases and realistic example queries that tell an agent when this tool is appropriate, such as year-over-year comparisons and climate research. However, it does not explicitly contrast it with alternatives or state when not to use it.

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