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

Annotations already establish the safe, read-only, idempotent profile, so the burden is light. The description goes further by enumerating the returned metrics (mention rate, share of voice, average position, citation share, sentiment, period-over-period change) and clarifying the by=question output, which matters given there is no output schema.

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?

Three dense sentences, front-loaded with the core purpose and then the mode semantics. No filler, though the framing clause in sentence one is slightly padded.

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 correctly carries the return-value burden and does so for both modes. It is complete enough to call the tool correctly, with only minor gaps like pagination or result-size behavior.

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 baseline is 3, but the description adds real meaning to the enum parameter by differentiating what by=engine versus by=question actually returns. It also confirms the default engines behind the engines filter, which the schema only gestures at.

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 measure (mention rate of the brand) and the exact engines covered, and explains the two output modes, so the resource is unambiguous. It never names or contrasts a sibling, so it falls short of a 5.

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?

It gives contextual framing ('when buyers ask about its category') and explains how to choose between by=engine and by=question, which is useful in-tool guidance. However, it never says when this tool should be chosen over sibling analytics tools such as get_competitors or get_citations, leaving cross-tool selection to inference.

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