get_email_stats

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

With no annotations, the description must carry the burden of disclosing behavior. It does so partially by listing the data fields and mentioning the date format, but it does not explicitly state that this is a read-only operation with no side effects, nor does it explain the behavior of omitted end_date. This is adequate but not comprehensive for a tool with zero annotation coverage.

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 that quickly communicates the tool's purpose and key parameters. Every element—metrics, date format, aggregation options—earns its place, with no filler or redundancy.

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?

The tool is relatively simple with three parameters and no output schema. The description lists the returned metrics, which partially compensates for the lack of output schema. However, it is silent on the end_date parameter's behavior and any response structure, leaving minor gaps for a complete understanding.

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 0%, so the description must compensate. It does by specifying the exact format for start_date (YYYY-MM-DD) and the allowed values for aggregated_by (day|week|month). However, it fails to explain end_date's semantics (e.g., default behavior). The added meaning is substantial for two of three parameters.

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 states that this tool retrieves global email statistics, listing specific metrics (requests/delivered/opens/clicks/bounces/spam). This is a specific resource with a clear scope ('global') and is easily distinguished from sibling tools like send_email or list_templates which serve different purposes.

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 clear context for when to use this tool, such as retrieving aggregated email stats over a date range. It does not explicitly name alternatives, but given none of the sibling tools cover stats, the usage intent is unambiguous. It also clarifies the aggregation options, guiding the user on how to tailor the request.

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