Solar irradiance and climate at a point

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

Annotations already declare the tool safe (readOnly, idempotent, non-destructive). The description adds valuable behavioral context: the data source (NASA POWER), the specific variables returned, and the daily temporal granularity. This goes beyond what annotations provide, though it does not mention potential limitations or date-range constraints.

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?

Two tight paragraphs: first establishes the core function, second lists returns and use cases. Every sentence provides useful information with no fluff. The structure front-loads the main purpose and uses bullet-style clarity in prose.

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?

With an output schema present, the description need not explain return formats. It covers the tool's purpose, variables, units, source, and application areas, which is sufficient for a read-only data retrieval tool. A slight gap is the absence of any mention of date-range behavior or limitations, but annotations and schema fill some of that.

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 description coverage is 100%, so the baseline is 3. The description adds minimal parameter-level detail beyond the schema, only implying lat/lon via 'any coordinate' and daily data via 'daily'. No additional syntax or format guidance is given, so it does not elevate the score.

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 states the tool returns daily solar irradiance and climate variables from NASA POWER for any coordinate, listing specific variables and units. This clearly identifies the resource (NASA POWER) and the scope, distinguishing it from sibling tools like weather forecast or air quality.

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?

Explicit use cases are provided ('solar energy siting, agricultural planning, historical climate analysis'), giving clear context for when to use the tool. However, it does not explicitly contrast with alternative siblings (e.g., get_weather_forecast for forecasts), so it lacks exclusionary guidance.

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