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

With no annotations provided, the description carries the behavioral disclosure burden. It does disclose the output contents and the 24-hour horizon, which is useful. But it does not define what the 'verdict' means, how the forecast is derived, or any edge-case behavior, so transparency is only partial.

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?

One dense, well-ordered sentence front-loads the purpose and lists the output components naturally. Every clause earns its place with no filler or repetition.

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 one-parameter lookup with no output schema, the description names all three return elements and the input convention, so an agent has enough to call it correctly. Minor gaps—such as verdict semantics and latitude range—keep it from being fully complete.

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 does by explaining that latitude is in geographic degrees and gives a concrete example (48.2 for Vienna), while also tying it to the output. It omits the valid range and sign convention, but for a single common parameter this is adequate.

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 names a specific deliverable (an aurora visibility outlook) and its three components: needed Kp, expected max Kp in 24 hours, and a verdict. This clearly distinguishes it from siblings like get_current_kp or get_kp_forecast_3day, which are general instead of latitude-specific.

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 intended use is implied: call this when you need a location-specific aurora visibility outlook rather than raw Kp readings or a general forecast. However, the description never explicitly says when to use this over the sibling tools, leaving the agent to infer the boundary.

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