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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds value by stating the exact return content (name, data type, description) and the purpose of pre-querying. This goes beyond what the annotations provide and helps an agent understand the tool's output.

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 two short sentences. The first sentence states the action and return fields; the second gives usage guidance. Every word earns its place, no fluff or repetition.

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 no output schema, the description adequately explains return values and connects to the query_dataset workflow. The single parameter is well-documented in the schema. Minor gaps like whether the field list is sorted or limited are not critical for this simple, read-only metadata operation.

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 has 100% coverage for the single parameter dataset_id, including its format ('portal:id') and how to obtain it ('Obtained from search_datasets results'). The description does not add additional parameter semantics beyond this, so the baseline score of 3 applies.

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 'List' with a clear resource 'fields of a dataset' and specifies the output fields (name, data type, description). It clearly distinguishes this tool from siblings like get_dataset_info or query_dataset by its focus on schema inspection rather than dataset metadata or data retrieval.

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 the tool: 'Call before query_dataset to know which fields and filters are available.' This provides clear contextual usage, though it does not mention exclusions or alternative tools explicitly. The sibling context is enough to infer alternatives.

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