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

The description discloses critical behavioral traits beyond the annotations, namely the types of status values (`active`, `suspended` for persons, `retired` for agents) and the persistence of these statuses for historical attribution. This prevents the agent from making incorrect assumptions about the data state.

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 definition is efficiently structured. It front-loads the core concept and uses the second sentence to deliver a dense, essential piece of business logic regarding status, making every sentence contribute meaningful context.

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 that the tool is simple (1 parameter, no output schema), the description is exceptionally complete. It covers the entity types, the filtering mechanism, and the vital status definitions, ensuring the agent has all necessary context.

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 coverage is 100%, so the primary parameter is adequately documented by the schema itself. The description simply repeats the option to filter by name, adding no semantic value beyond what the structured data provides. Baseline score is appropriate.

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 identifies the purpose as listing members, explicitly distinguishing between 'humans' and 'agents.' This prevents ambiguity for the AI agent when choosing the correct roster-based tool.

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 it does not name a competing sibling tool, it provides clear guidelines on how to use the data responsibly, specifically advising the agent to check the `status` before assuming a member is active. This is crucial for correct operational workflow.

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