site_score

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

With no annotations, the description carries the full burden of behavioral disclosure. It clearly states that each call runs a live satellite computation and takes 25-40 seconds, which is a significant behavioral trait. It also mentions that the 'full' detail option is 'considerably larger', implying a larger response. This adds value beyond the schema, though it does not detail side effects or requirements, but for a read-only analysis tool, this is sufficient.

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 well-structured with a clear purpose in the first sentence, followed by use cases, performance notes, and parameter explanations. It is slightly long but every sentence adds value; the parameter section could be more concise, but the overall structure is front-loaded and efficient.

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?

The tool has 5 parameters, all explained in detail, an output schema exists (so return values are known from the schema), and it covers key context like performance and use cases. It lacks explicit mention of error conditions or prerequisites (e.g., valid coordinates), but given the output schema and comprehensive description, it is largely complete for an agent to invoke correctly.

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 0%, so the description must compensate. It does explain lat and lon as a point, radius_m as the analysis radius, month as seasonal evaluation with an annual default, and detail as summary vs full with raw diagnostics. This adds meaning beyond the basic type definitions, though it does not give specific units for some metrics or explain the 'full' diagnostics in detail. The baseline for 0% coverage is higher, and this description meets it well.

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 scores a geographic coordinate for ecological and agricultural land suitability, with a specific verb ('score') and resource (geographic coordinate). It lists the per-metric breakdown, distinguishing it from potential weather or property tools, and its use cases. This is specific and goes beyond a tautology, making it easy for an agent to understand the tool's core function.

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 lists use cases (site selection, agtech, conservation) and states what it is NOT (not a weather forecast, not property-value estimate), which helps with when-to-use and when-not-to-use. It also advises on performance (prefer one call over several, smaller radius for speed), giving practical usage guidance that is not available from the schema.

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