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

The readOnlyHint annotation already establishes that this is a safe read operation, and the description adds useful behavioral context about the fields returned and the fallback_if_omitted value. It does not discuss auth, pagination, or failure modes, but for a zero-parameter read tool that is a minor gap.

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 purpose is front-loaded in the first sentence, and the subsequent sentences add usage conditions and fallback semantics without redundancy. Every clause contributes directly to selecting or interpreting the tool.

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?

With no output schema, the description carries the burden of explaining return values, and it does so by listing the fields and describing fallback_if_omitted. This is sufficient for an agent to understand what the tool returns and why it matters.

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?

There are no input parameters, so parameter semantics are not applicable and the baseline is 4. The description does not need to compensate for any schema gap.

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 (List) and resource (brand kits) and scopes it to the user's active space. It also enumerates the returned fields, making the tool's purpose distinct from sibling list operations.

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 explicit conditions for calling: before generating a social image, email, or PDF for a non-default brand, and when the user asks which brands they have set up. It does not name alternatives or state when not to call, so it stops short of the top score.

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