get_email_stats

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

The description clearly indicates a read-only behavior ('Return aggregate mailbox statistics') and describes the output. Although no annotations exist, the description adequately conveys the non-destructive nature, though it could explicitly mention read-only status.

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 three-sentence description is concise, front-loaded with purpose, and ends with usage alternatives—no superfluous words.

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 no parameters, no output schema, and no annotations, the description provides sufficient context: what it returns, when to use it, and how it compares to related tools.

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?

With zero parameters and 100% schema coverage, the baseline is 4. The description adds value by detailing the output fields (folder counts, unread, analytics sample), which compensates for any lack of parameter info.

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 the tool returns aggregate mailbox statistics including folder counts, unread counts, and an analytics sample, and explicitly contrasts with siblings get_email_analytics and get_volume_trends, ensuring unambiguous purpose.

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 explicitly states when to use this tool ('quick mailbox health overview') and directs users to preferred alternatives for richer data ('Prefer get_email_analytics... Prefer get_volume_trends...'), providing excellent guidance.

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