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

Annotations already establish safety and idempotence (readOnlyHint, openWorldHint, idempotentHint, destructiveHint: false). The description adds useful behavioral context beyond annotations, including per-dataset freshness, latest model run, and the fact that datasets vary by CONUS/Alaska/Hawaii domain, without contradicting any annotation.

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?

Three sentences front-load the core behavior, then provide practical usage guidance and a concrete example. Every sentence earns its place and there is no redundant restatement of schema or annotations.

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 full input schema, an output schema, and annotations covering safety and idempotence, the description adds the remaining needed context: what datasets are listed, why the freshness matters, how to use it with related tools, and a concrete invocation example. This is complete for correct tool selection and invocation.

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?

The input schema already provides 100% coverage with detailed descriptions of lat, lon, location, and include_freshness, so the description is not required to repeat parameter details. The description adds no substantive parameter meaning beyond the example location, which is sufficient given the schema coverage.

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 uses a specific verb ('Discover') and a specific resource ('datasets available at a location'), naming the dataset categories (model grids, analyses, observations) and the freshness information returned. It is clearly distinct from siblings like get_forecast or query_dataset, and it also explains its downstream relationship to query_dataset and describe_dataset.

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 states when to use this tool: to find dataset_id values for query_dataset/describe_dataset and to assess data currency. It does not explicitly describe when not to use it, but the intended use cases are clear enough to guide selection among a large sibling set.

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