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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds useful context by saying what is returned — fields, types, notes — which matters because there is no output schema. It says nothing about what happens when the dataset name is unknown, however.

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?

Two short sentences, no filler, and the core action is front-loaded ahead of the optional narrowing behavior. Every clause carries information.

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?

For a two-parameter read-only tool with no output schema, the description covers both what is returned and how the optional parameter behaves. Only edge-case behavior for an unknown or missing dataset is left unstated.

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 only 50%, and the schema documents 'dataset' tersely as 'A dataset name.' The description compensates for the undocumented 'search' parameter by explaining it narrows fields by words in names or notes, which is meaning the schema does not carry.

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 and resource: it returns a dataset's fields, their types, and the notes on them. That is clearly distinct from sibling readers such as list_datasets or get_field_values, though it never names those siblings to reinforce the contrast.

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 second sentence gives real guidance on how to use the search parameter, but there is no statement of when to reach for this tool versus list_datasets, get_field_values, or note_field / note_dataset. Usage is implied by the verb rather than explained.

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