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

Annotations already cover the safety profile (readOnly, non-destructive, closed-world), so the description adds real value: it discloses the conditional presence of stored fact-check and objection analyses, and it flags that a sentiment scale plus a thin-sample caution ship in the `howToRead` field of the response. That metadata hint is exactly the kind of behavioral context an agent needs to interpret low-volume data, though return shape/pagination is not described.

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 payload inventory is front-loaded and densely packed into one sentence that maps to distinct output sections, followed by a short pointer to `howToRead`. It is efficient for the amount of content covered, though the single mega-clause makes it slightly harder to scan than a short bulleted structure would.

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 and four optional parameters, the description carries the burden of explaining what comes back, and it does so section by section, including conditional elements. It is nearly complete; the only omission is how the clientId/projectId scope defaults interact, which the schema partly covers.

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 the baseline is 3. The description only restates that `days` and `engine` are filters and adds nothing about `clientId`/`projectId` scope resolution. Notably, the schema's engine fallback behavior (reverting to all engines when a label has no described mentions) is documented in the schema rather than the prose, so the description adds no meaning beyond it.

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 concrete resource and enumerates the payload precisely: clustered descriptive terms with counts and per-brand share, distinctive terms, brand-level sentiment, cited source pages, and stored fact-check/objection analyses. That is far more specific than a restated title. It stops short of a 5 because it never names a sibling it must not be confused with, notably get_citations, which also returns cited pages.

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?

Usage is only implied: the agent can infer this is the tool for brand-attribute/perception analysis, and the second sentence names the two filters (days, engine). There is no explicit when-to-use guidance, no statement of when to prefer get_insights or get_ai_visibility_metrics instead, and no prerequisites mentioned.

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