get_solar_energetic_particle

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves data (implying a read-only operation) and mentions date parameters with defaults, but lacks critical details: it doesn't specify data format, source, rate limits, authentication needs, error conditions, or whether it's a real-time or historical query. For a data retrieval tool with zero annotation coverage, this is insufficient.

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 appropriately sized and well-structured: a clear purpose statement followed by a parameter list with concise explanations. Every sentence adds value—none are redundant or vague. It could be slightly more front-loaded by integrating parameter hints into the main sentence, but overall it's efficient and readable.

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 solar data retrieval, no annotations, and no output schema, the description is incomplete. It covers parameters well but omits essential context: output format (e.g., JSON, CSV), data granularity, source reliability, error handling, and how it differs from sibling solar tools. Without this, an agent might struggle to use the tool effectively or interpret results.

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 description adds significant value beyond the input schema, which has 0% description coverage. It explicitly defines both parameters ('start_date' and 'end_date'), specifies their format ('YYYY-MM-DD'), and provides default behaviors ('Defaults to 30 days before current date' and 'Defaults to current date'). This fully compensates for the schema's lack of descriptions, making parameter usage clear.

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 the tool's purpose: 'Get solar energetic particle (SEP) data.' This specifies the verb ('Get') and resource ('solar energetic particle data'), making the function unambiguous. However, it doesn't differentiate from sibling tools like 'get_coronal_mass_ejection' or 'get_solar_flare' that also retrieve solar event data, which prevents a perfect score.

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 no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_coronal_mass_ejection' or 'get_solar_flare' for comparison, nor does it specify use cases, prerequisites, or exclusions. The only implicit context is the date parameters, but this doesn't constitute meaningful usage guidance.

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