get_email_stats

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

Beyond the readOnlyHint annotation, the description discloses important behavioral traits: it reads from the local index rather than live IMAP, auto-refreshes if stale or empty, and may lag behind changes made in another client. It also explains the specific lag condition for unread counts, adding substantial transparency.

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 front-loaded with the core purpose, then gives usage guidance, then adds necessary caveats about data freshness. Every sentence earns its place; there is no redundant filler or repetition of schema information.

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 read-only tool with two optional parameters and no output schema, the description is complete: it explains what is returned, when to use it, what alternatives exist, and the data-source caveats that affect interpretation. No critical context is missing.

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 already fully describes both parameters with 100% coverage: 'days' as 'Trailing days window' and 'limit' as 'Maximum messages to sample.' The description does not add parameter-level meaning beyond this, so 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 opens with a specific verb and resource: 'Return aggregate mailbox statistics: folder message counts, total unread counts, and a brief analytics sample.' It clearly distinguishes itself from sibling tools by explicitly naming get_email_analytics and get_volume_trends as richer alternatives.

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 states exactly when to use this tool ('Use for a quick mailbox health overview') and explicitly directs users to alternatives: 'Prefer get_email_analytics for richer breakdowns... Prefer get_volume_trends for time-series daily volume data.' This is exemplary usage guidance.

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