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

The annotations already establish read-only and open-world behavior, and the description adds substantive context beyond them: the data source (World Bank / Solargis), a clear limitation ('not a yield guarantee'), and precise payment semantics ($0.002 USDC per successful call via x402, with failed calls not charged). It does not mention rate limits or latency, but covers the key behavioral traits an agent needs before calling.

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 three dense sentences with no filler: it front-loads what data is returned, then adds the important caveat, then the payment model. Every sentence contributes actionable information for an agent deciding whether and how to call the tool.

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 low complexity (two fully documented parameters), existing output schema, and annotations covering safety, the description is nearly complete: it covers data source, returned variables, usage caveat, and payment details. The main omission is explicit sibling differentiation, which could matter for selecting between this and energy_pvwatts_solar_simulator.

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 both lat and lon fully described including ranges and examples, so the structured fields carry the parameter documentation burden. The description adds only that the call is for 'one latitude and longitude,' implying a single-point lookup rather than batch input, which is a marginal addition.

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 names a specific resource (Global Solar Atlas long-term average solar data) at a specific spatial unit (one latitude/longitude) and enumerates the returned fields: PV output, GHI, DNI, diffuse irradiation, and air temperature. It clearly distinguishes itself from general energy tools, but does not explicitly name or differentiate from the closest siblings, energy_pvwatts_solar_simulator and energy_global_wind_atlas_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 implies use for long-term solar resource screening and includes a caveat that it is 'not a yield guarantee for a specific plant,' which hints at when not to rely on it for bankable yield estimates. However, it never explicitly says when to use it versus alternatives such as energy_pvwatts_solar_simulator, which offers a more detailed PV simulation.

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