get_geomagnetic_storm

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 describes a read operation ('Get') and specifies date parameters with defaults, but doesn't cover critical aspects like data format, rate limits, authentication needs, error handling, or whether the tool is idempotent. For a data retrieval tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 front-loaded. The first sentence states the core purpose, followed by a structured 'Args:' section that efficiently documents parameters without redundancy. Every sentence earns its place, and there's no wasted verbiage or unnecessary elaboration.

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 moderate complexity (2 parameters, no output schema, no annotations), the description is partially complete. It excels in parameter documentation but lacks context on output format, data scope, or integration with sibling tools. Without annotations or output schema, the agent won't know what the returned data looks like or how to handle it, leaving gaps in overall usability.

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 substantial meaning beyond the input schema, which has 0% description coverage. It explicitly documents both parameters ('start_date' and 'end_date'), their formats ('YYYY-MM-DD'), and default behaviors ('Defaults to 30 days before current date' and 'Defaults to current date'). This fully compensates for the schema's lack of descriptions, providing clear and complete parameter semantics.

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 geomagnetic storm (GST) data.' It specifies the verb ('Get') and resource ('geomagnetic storm data'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_coronal_mass_ejection' or 'get_solar_flare', which likely retrieve related but distinct space weather data.

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 or contexts where geomagnetic storm data is preferred over other space weather data (e.g., solar flares or coronal mass ejections). The only implied usage is retrieving GST data within a date range, but no exclusions or prerequisites are stated.

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