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

The description adds useful context by clarifying that the POST endpoint is actually a read-only query, which complements the readOnlyHint annotation. It still omits operational details such as default date-range behavior, error handling, authentication needs, and pagination or response shape, so the behavioral disclosure remains moderate.

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 two tightly written sentences with the core purpose front-loaded. The endpoint parenthetical is compact and helps resolve the POST-versus-read ambiguity without unnecessary verbosity.

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 three-parameter read-only analytics tool with full schema coverage and annotations, the description gives enough context to invoke it correctly and understand the returned metrics. It could be stronger by stating what happens when the date range is omitted, but the essential information is present.

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 the schema already documents campaign_id, start_date, and end_date semantics. The description reinforces that the date range is optional and tied to one campaign, but adds no format or constraint details beyond what the schema provides.

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 states a specific resource and metric set: daily delivery and credit-usage statistics for one campaign, including sent, delivered, read, failed counts, and credit usage. It is clearly more specific than the tool name alone, though it does not explicitly contrast the tool with siblings such as get_api_campaign or list_campaigns.

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 optional date range is mentioned, implying the tool can be used for campaign analytics over a period. However, there is no explicit guidance on when to use this versus campaign detail or campaign listing tools, and no stated prerequisites or exclusions.

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