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 mentions the source (official NOAA) and the output semantics (maximum expected Kp per day, Europe/Berlin days), which provides some insight. However, it does not describe the response format, update frequency, or any limitations. For a simple tool with no parameters, this is acceptable but not comprehensive.

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, information-dense sentence with zero redundancy. Every element — the source, the time frame, the metric, and the timezone — earns its place, and the key attribute (3-day forecast) is front-loaded.

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 tool's simplicity (no parameters, no output schema, no nested objects), the description covers the essential context: it is a forecast, the metric is Kp, and the days are Europe/Berlin. It does not need to explain return values since there is no output schema, and the absence of parameters means no parameter documentation is required. The only minor omission is a note on the forecast's update cadence, but that is not critical for correct invocation.

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?

The tool has zero parameters, so there is nothing for the description to explain. Per the guidelines, a score of 4 is the baseline in this case, and since the description correctly focuses on the output rather than parameters, it fully satisfies this dimension.

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 it provides an 'Official NOAA 3-day geomagnetic forecast' and specifies the exact data: 'the maximum expected Kp per calendar day'. This is a specific verb-resource pair that distinguishes it from siblings like get_current_kp (current conditions) and get_solar_flares_24h (solar flares), making its purpose unambiguous.

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 implies usage by its focus on a 3-day forecast, but it does not explicitly state when to choose this tool over its siblings or when not to use it. For instance, it doesn't mention that get_current_kp is for real-time Kp values. The guidance is adequate but left to the agent's inference instead of being explicit.

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