Get real-time solar wind conditions

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

With no annotations provided, the description carries the full burden. It discloses the data source (L1), units, physical significance of Bz, and the lag relationship to Kp. It doesn't discuss error states or rate limits, but for a zero-parameter read-only tool this is sufficient.

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 dense sentence followed by a usage sentence. Every clause adds value: the Bz explanation is important for understanding why this data matters. Slightly long, but not wasteful.

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 there is no output schema, the description enumerates the return fields fully. It also provides scientific context, units, and usage scenarios, making it self-contained for an agent to invoke correctly.

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 the baseline is 4 per the rubric. The description focuses on output semantics, which is appropriate since there are no inputs to clarify.

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 ('Returns') with a clear resource ('current real-time solar wind reading at L1') and enumerates the exact measurements (Bt, Bz, speed, density, temperature). It also differentiates from sibling tools by explaining its role as upstream driver data for Kp forecasts.

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 when-to-use scenarios: when asked 'what's the solar wind doing' or 'is Bz south', and when get_band_conditions/get_kindex_forecast answers need upstream driver data. It also adds the 30-60 minute lead time context, which helps an agent reason about temporal relationships.

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