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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds useful detail about the aggregate nature of the data and explicitly excludes billing figures, but it does not discuss return formatting, pagination, or any operational behavior beyond the counts themselves.

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 a single sentence that front-loads the core concept and then lists specifics with an em dash. Every word adds information, and there is no filler or repetition of the tool name or title.

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 the tool has no parameters and an output schema exists, the description fully covers what an agent needs to know: what metrics are included, that it is counts-only, and that billing figures are absent. Nothing required for correct invocation is missing.

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 tool has zero parameters, so there are no parameter semantics for the description to clarify. The description appropriately stays focused on what the tool returns, which is the correct role for a no-input endpoint.

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 resource (workspace usage) and enumerates the specific metrics returned, such as signals, active sources, posts monitored, and discovery runs. It is not a tautology and the scope is obvious, but it does not explicitly differentiate itself from sibling tools like list_signals or get_signal.

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 phrase 'Workspace activity counts' implies this tool is for high-level usage metrics rather than detailed data, and 'Counts only, no billing figures' sets an expectation boundary. However, it does not explicitly state when to choose this tool over alternatives or mention exclusions relative to sibling tools.

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