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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds one genuinely useful behavioral fact: results are expressed as share of answers relative to this brand's own share, implying a comparative ranking. It does not disclose ordering, behavior when no prompts are tracked, or what an empty result means.

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?

A single sentence with no filler, and the comparative share framing is placed up front rather than buried. The awkward word order costs a little clarity but nothing is redundant.

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?

This is a simple two-optional-parameter read tool, but with no output schema the description is the only source for what the response looks like, and it gives only a loose sketch (brands plus share values). It also omits the dependency on tracked prompts, which an agent needs to know before calling it.

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%, with both limit and engine fully documented including the allowed engine values, so the baseline is 3. The description adds no syntax or semantic detail about either parameter — notably it never mentions that results can be scoped to a single engine, even though it refers to "AI engines" generally.

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 conveys the resource — brands that AI engines mention in answers to tracked prompts, with their share next to this brand's own share — but the phrasing is grammatically awkward ("Brands AI engines name") and never states a verb like returns or lists. It also fails to distinguish itself from close siblings such as get_ai_visibility, get_brand_perception, and get_competitor_gaps.

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?

There is no when-to-use guidance, no preconditions (e.g., that tracked prompts must exist via set_tracked_questions), and no mention of when a sibling tool would be the better choice. The agent must infer the use case entirely from the resource description.

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