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

The annotations already mark the call read-only and non-destructive, but the description adds significant behavioral facts: it exposes members' email addresses, notes that the workspace belongs to AIsa rather than the caller, and warns about ~16-second latency. These are meaningful details not inferable from annotations alone.

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?

Three tightly written sentences: one for output shape, one for the use case, and one for caution/performance. Every sentence earns its place with no filler or redundant schema 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?

An output schema exists, so return values need no further explanation. Combined with the use case, sensitivity warning, and performance caveat, the description gives an agent everything needed to select and safely invoke this tool.

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 description coverage is 100%, so page and per_page are already fully documented. The description adds no extra parameter semantics, which aligns with the baseline of 3 for high schema coverage.

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 identifies the resource (user accounts in the Apollo workspace) and the returned structure (users array with id, name, email, credits, pagination), while the title supplies the 'list' verb. No sibling tool covers user accounts, so it is clearly distinguishable.

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?

It gives a concrete use case: resolving an owner_id from contacts, accounts, or deals into a person. It also cautions about exposing workspace members' emails and workspace ownership, which helps the agent judge appropriateness. It doesn't name alternatives, but no sibling tool lists users, so that's acceptable.

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