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

Annotations already declare readOnly, idempotent, non-destructive and open-world, so the safety profile is covered. The description adds real value beyond that: deduplication semantics across the window, the DAU/MAU stickiness formula, and per-day granularity of rolling windows — behavioral context the annotations do not convey.

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 tight sentences: the first front-loads what is returned, the second adds the differentiating semantics. No filler, no restatement of the title.

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 necessary work of naming the returned series (DAU/WAU/MAU plus stickiness per day). Given 100% schema coverage and rich annotations, little else is needed; only the relationship to sibling analytics tools is 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 description coverage is 100%, so app, range, filters and environment are all fully documented in the schema. The description only lightly echoes the range parameter ('for each day in the range') and adds no syntax or default detail, which is the correct baseline when the schema does the work.

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 the specific resource (daily/weekly/monthly active users) plus the derived metric stickiness with its formula, so the agent knows exactly what data comes back. The contrast with 'visitors' hints at what it is not, but no sibling tool is named, so differentiation is implicit rather than explicit.

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 'Unlike visitors these are deduplicated... and measure ongoing engagement' clause implies when this tool is preferable to a visitor-counting read, but there is no explicit when-to-use, when-not-to-use, or named alternative among the many analytics siblings (get_metric_series, get_timeseries, get_analytics_overview).

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