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

Annotations already mark the tool read-only, idempotent, open-world, and non-destructive. The description adds useful context: MIT licence, no auth, no upstream cost, and the constraint that all points share a single dataset. It doesn't cover rate limits or error behavior, but the safety profile is well handled by 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?

Four sentences, front-loaded with the core function, and each sentence carries distinct information: request scope, dataset constraint, return format, then use cases plus license/auth/cost. No filler or repetition of schema details.

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?

With a fully documented schema, an output schema available, and annotations covering safety, the description supplies request shape, use cases, licensing, and auth requirements. It omits a comparison with sibling point/high_res/ocean tools and error behavior, but these are not necessary for correct invocation in most cases.

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 description coverage is 100%, so the schema already documents all three parameters with ranges, enums, defaults, and array bounds. The description reinforces the shared-dataset constraint and describes the result shape, but adds no substantially new parameter semantics beyond this, warranting the baseline score.

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 opens with a specific verb and scope: 'Get land surface elevation for up to 100 lat/lon coordinates in a single request.' It clearly distinguishes this batch tool from sibling point queries and enumerates the return fields (elevation_m, lat, lon, dataset). No ambiguity about the operation.

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?

It names concrete use cases ('elevation profiling along a route, contour-line computation, or bulk terrain analysis') that signal when batch is appropriate. It doesn't explicitly exclude single-point alternatives like opentopodata.elevation.point or mention when to prefer high_res/ocean, so it stops short of full when-not guidance.

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