solar-intel

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

Without annotations, the description discloses key behaviors: returns specific irradiance components and a panel yield estimate for a 1 kW system, states data source (Open-Meteo), and notes it is free with no API key or rate limits. It does not discuss failure modes or edge cases, but the provided details cover core behavioral traits adequately.

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 four sentences long, each serving a distinct purpose: stating the function, listing outputs, noting use cases, and providing competitive context. It is front-loaded with the main action and resource, and contains no redundant or unnecessary information.

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 simplicity of the tool (no output schema, few parameters), the description covers the essential aspects: what it does, what it returns, use cases, and data source. It lacks discussion of error handling or limitations, but for a straightforward data retrieval tool, the description is reasonably complete.

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 is 100% with each parameter described. The description does not add significant new parameter information beyond what's in the schema; it simply reinforces that location can be a name or lat/long. Baseline score of 3 is appropriate as the description adds no additional parameter meaning.

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 it performs 'solar irradiance analysis and 7-day forecast for any location' and lists specific outputs like GHI, DNI, DHI, peak sun hours, etc. It distinguishes itself from sibling tools like general weather by focusing exclusively on solar data and enumerating use cases (rooftop solar, agriculture, EV charging, energy markets).

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 explicitly mentions domains where the tool is useful (solar feasibility, agricultural planning, EV charging, energy market analysis), providing clear context for when to use it. It does not explicitly mention alternatives or exclusions, but the use cases implicitly guide selection among siblings like weather or weather-history.

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