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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It communicates that this is a non-mutating read operation and names the fields involved, which is useful. However, it does not disclose permissions, error behavior, response format, or whether the operation is scoped to the active organization beyond what the schema already indicates.

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 front-loaded sentence with no filler words. It states the verb and the specific data returned in under six words, which is appropriately sized for a tool of this low complexity. Every word 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 one-parameter read tool with no output schema, the description is minimally sufficient: it tells the agent what the tool reads, and the required parameter is fully documented in the schema. However, it leaves gaps around the meaning of 'marketing state,' the exact response shape, and when to prefer this tool over the update sibling. These gaps make it adequate but not complete.

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 provides 100% coverage of the single parameter, describing `organization_id` as 'Active organization ID.' The description itself adds no parameter-level details beyond what the schema already documents. With full schema coverage, the baseline score of 3 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 uses the specific verb 'Read' and names the exact data returned (timezone and marketing state), making the tool's function clear. It is naturally distinguished from the sibling `commsharbor_messaging_settings_update` by framing this as a read operation. However, it does not explicitly state the organization-level scope or reference any alternative tools, so it stops short of full differentiation.

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 description provides no guidance about when to use this tool versus alternatives such as `commsharbor_messaging_settings_update` or `commsharbor_contact_marketing_get`. It relies entirely on the verb 'Read' to imply usage, but there are no explicit conditions, exclusions, or alternative names mentioned. An agent must infer appropriate usage from the tool name and sibling list.

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