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

Annotations already establish that this is a read-only, closed-world operation (readOnlyHint=true, openWorldHint=false). The description adds value by listing the fields returned, which partially compensates for the missing output schema. However, it does not disclose pagination, ordering, or whether inactive members are included.

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?

A single, front-loaded sentence with no filler. The parenthetical field list is compact and informative. Every element earns its place.

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 zero-parameter, read-only list tool with no output schema, the description supplies the essential return fields and the basic domain context. It is nearly complete, though minor operational details such as ordering or membership scope are omitted.

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?

This tool has zero parameters, so there are no parameter semantics to document. Per the scoring rule, an empty parameter set yields a baseline of 4; the description appropriately does not invent or repeat parameter details.

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 states a specific verb ('List') and resource ('AI members of this Bordet boardroom'), and parenthetically enumerates the returned fields (name, role, model, capabilities). It clearly distinguishes the tool's purpose from siblings, though it does not explicitly name or contrast with any alternative.

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?

No when-to-use guidance, prerequisites, or alternatives are provided. The description only states what the tool does; an agent must infer that it should call this tool whenever member information is needed. This matches the 'no guidance' level from the calibration example.

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