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

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, so the safety profile is covered. The description contributes the shape of the result (which metrics are returned, one grouping dimension at a time), but says nothing about defaults beyond the period, volume/row limits, or how results behave with no filters at all.

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, zero filler, with the metric inventory front-loaded and the grouping caveat trailing. Nothing is repeated from the schema or annotations.

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 59 optional parameters, no required fields, and no output schema, the description does partially substitute for a return-value spec by listing the metrics. It is still too lean for a tool of this breadth: how multiple filters combine, what happens with an empty filter set, and the default period interplay are left unstated.

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 86%, so most of the 59 filter parameters — including the permission caveat on 'user' and the date_mode attribution semantics — are already documented in the schema. The description adds one genuine constraint the schema lacks: grouping is limited to a single dimension per call. That is useful but thin against such a wide parameter surface.

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 names the resource precisely (aggregated click/conversion analytics with an explicit metric list) and the aggregation dimension, so an agent knows it returns summary numbers rather than rows. It does not, however, distinguish itself from near-siblings such as get_report, get_cohorts, get_push_analytics, or report_meta_stats, which also produce aggregates.

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?

"Aggregated analytics for a period" implicitly signals that this is the tool for summed/totalled figures rather than raw event lists like list_clicks or list_conversions. No explicit when-to-use/when-not guidance or named alternative is given, so an agent facing get_report or get_cohorts must guess.

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