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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, covering safety. The description adds non-obvious behavioral constraints: the 0.5° × 0.5° bounding box limit ingests geographic limits, and the 'free registration (5K req/day)' warns about rate limits. It also lists output fields, providing transparency about response contents without contradicting annotations.

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 concise and front-loads the core purpose, then provides constraints and context. Every sentence adds value: purpose, limits, return fields, use cases, and sourcing/rate info. No redundant fluff, though the list of use cases could be omitted, but it aids selection.

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 moderate complexity (5 params, output schema, dataset enum), the description covers purpose, constraints, use cases, source, and rate limits. It does not explain each parameter, but the schema does that. It lists returned fields, though an output schema already exists surrendered context. The missing info is minimal.

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 per-parameter descriptions. The description adds the critical constraint that the bounding box cannot exceed 0.5° × 0.5°, which is not present in the schema and directly affects the four required coordinate parameters. This adds meaningful semantic beyond the schema baseline.

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 a specific verb ('Get') and resource ('terrain elevation statistics') with a clear scope ('for a bounding box area'). It distinguishes this from point-elevation tools by emphasizing the area-based aggregation and the specific metrics returned (min, max, mean, range). The phrase 'using global DEM datasets' further clarifies the data source domain.

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 provides clear context by listing relevant use cases ('hydrological analysis, terrain characterisation, and infrastructure siting') and the maximum bounding box constraint. However, it does not explicitly name alternative tools or state when not to use this tool, so it lacks explicit exclusions despite having strong contextual guidance.

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