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

Annotations already declare readOnly, idempotent and non-destructive, so the safety profile is covered. The description still adds a non-obvious trait — days without data are omitted rather than zero-filled — plus the week-keying convention (Monday) and month format, though it says nothing about response shape or volume/pagination.

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?

Metrics and granularity are front-loaded, followed by usage and then a caveat, which is good ordering. The English sentence is then duplicated verbatim in Portuguese, doubling length without adding information for an English-reading agent.

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 an 11-parameter read tool with no output schema, the description states the returned metrics, grouping dimensions, and gap behavior, which covers what an agent needs to interpret results. Date-window mechanics and defaults live in the schema, so nothing critical 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?

Schema coverage is 100%, so the schema carries the parameter documentation and baseline is 3. The description adds genuine value beyond it for granularity (Monday as week key, yyyy-mm for month) and confirms filtering, but the other nine parameters are documented only in 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?

Names the exact metrics returned (clicks, impressions, CTR, position) and the three time groupings, which tells an agent precisely what this retrieves. It does not name a sibling it competes with (e.g. get_breakdown, get_site_summary), so differentiation is inferred from the time-series framing rather than stated.

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?

Gives explicit activation contexts: trend, seasonality, and locating the date of a drop. That is enough to route an agent here for time-oriented questions, but there are no exclusions or named alternatives for adjacent cases like anomaly detection or change points.

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