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

Annotations already declare readOnly, openWorld, idempotent, non-destructive hints. The description adds value by specifying the exact metadata returned (columns, types, row count, category, last-updated). No contradictions or missing behavioral traits noted.

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?

Single sentence efficiently conveys purpose, input, and output. No extraneous words. Front-loaded with the key action and resource.

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 no output schema, the description adequately lists the expected returned fields (columns, types, row count, etc.). However, it does not explain how to obtain the resource_id or any potential limitations. For a simple tool, this is sufficient.

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 a clear description of resource_id. The description reinforces the parameter with an example ('hmbh-c3hw'), adding semantic context beyond the schema. No other parameters exist.

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 gets schema and metadata for a Pierce County Open Data dataset by resource_id, with specific details like columns, types, row count. It includes an example, making the purpose unambiguous and distinct from sibling tools like query or datasets.

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?

While the description implies usage for retrieving dataset metadata, it does not explicitly state when to use this tool versus alternatives (e.g., query for data retrieval) or provide any conditions. The usage context is inferred but not guided.

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