get_solar_irradiance

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

With no annotations, the description carries the full burden. It discloses the external API (Open-Meteo) and the return unit (kWh/m²), but does not clarify the time period over which the 'average daily' value is calculated, nor does it mention error behavior, rate limits, or other caveats. This is adequate but not fully transparent.

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 two concise sentences that directly state the tool's purpose and return value. There is no redundant content, and key details are 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, the description is nearly complete: it names the data source, specifies inputs implicitly via schema, and provides the return unit. The only notable gap is the ambiguous averaging period for the 'average daily' radiation, which prevents a perfect score.

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 coverage for parameters is 100%, with clear per-parameter descriptions for latitude and longitude. The description adds value by specifying the output format (kWh/m²), but does not need to elaborate on parameter semantics since the schema fully covers them.

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 action ('Fetch') and the resource ('solar irradiance data') along with the geographic context ('for a geographic location'). It distinguishes itself from sibling tools that focus on calculations (e.g., 'calculate_solar_capacity') or saving/retrieving assessments by indicating it retrieves raw data from a specific API.

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: when you need solar irradiance data for a location, before downstream calculations. However, it does not explicitly state when to prefer this over alternatives or mention any exclusions, so the guidance is only implicit.

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