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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so safety is covered. The description adds real behavioral scope beyond that by enumerating the metrics returned and noting coverage across every send medium, though it says nothing about row limits or behavior on very wide date windows.

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?

Two sentences, no filler, with the core payload (what is broken down) front-loaded and the disambiguating contrast placed last. Every clause 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?

With no output schema, the description does the work of naming the returned metric set and the mediums covered, which is the key missing piece. Remaining gaps are minor: no note on output shape or date-range validation limits.

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 coverage is 100% with enum values and defaults documented, so the schema already carries the parameter burden. The description's 'day/week/month' phrasing loosely corroborates group_by but adds no format, default, or interaction detail beyond the schema.

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?

States a specific verb (Get) plus the exact resource (day/week/month breakdown of named email metrics) and scopes it to all send mediums. It also explicitly contrasts itself with the sibling get_analytics ('period totals'), so an agent can separate the two without opening either schema.

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 closing sentence gives clear selection context: this is the timeline/granular view, whereas get_analytics provides period totals. That is a usable routing rule, but there is no explicit guidance on when not to use it (e.g. date-range limits or fallback behavior).

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