get_upper_air

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

With no annotations provided, the description fully carries the burden of disclosure. It details the return structure (12-hour time series, height in dam, temperature, wind, relative/absolute vorticity in 10^-5 s^-1), explains the underlying model (global GFS via Open-Meteo) and grid spacing (~110km), and clarifies that it's not region-restricted. There are no contradictions or omissions.

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 introduction, usage cues, scientific context, and parameter details. It uses bullet-like formatting and line breaks for readability. However, it is relatively long; some sentences could be merged or trimmed without losing value, justifying a 4 rather than a 5.

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?

Given the complexity of an upper-air forecast tool with 3 parameters and an output schema (not shown), the description covers all necessary aspects: purpose, usage scenarios, scientific background, parameter behavior, and output details. It distinguishes itself from siblings like get_surface_analysis and get_spc_outlook, and the presence of an output schema reduces the need to describe return format further.

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 0%, so the description must compensate. It explains all three parameters: latitude and longitude can be omitted for a default location, and units are described in depth with examples ('us' or 'si' with field overrides like 'pressure:mb,wind:kt'). This adds significant meaning beyond the schema's basic types.

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 states 'Get 500mb upper-air forecast with heights, temperature, wind, and vorticity.' It specifies the resource (500mb upper-air forecast) and the verb (get), and the inclusion of derived quantities like vorticity distinguishes it from siblings like get_surface_analysis or get_forecast.

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 explicit 'Use when:' phrases like 'What does 500mb look like?' and 'Where are the troughs?', giving clear contextual cues. It also advises omitting lat/lon for default location and notes it is not US-only. However, it does not explicitly state when not to use or provide alternatives to this tool, which would elevate it to a 5.

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