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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is covered. The description still adds genuine value beyond that by enumerating the payload shape (overall score, per-engine breakdown, change since previous run) and by disclosing the 'runs left this period' quota signal. It omits what happens when no prompts are tracked or no run has completed yet.

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, front-loaded with the core measurement and followed by the return fields. Every clause carries information; there is no filler or 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 must carry the return-value burden, and it does by listing the four things returned. For a zero-parameter read tool with full annotation coverage that is close to sufficient; only empty-state and freshness behavior are 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?

The tool takes zero parameters, which is the baseline-4 case; there is nothing for the description to disambiguate. It correctly implies the only scoping is implicit (the brand and its tracked prompts), so an agent will not hunt for a missing brand_id argument.

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 names the specific resource and measurement: how often five named engines mention 'this brand' when answering its tracked prompts, plus the exact figures returned (0-100 score, per-engine score, delta, runs remaining). That is far more specific than a tautology. It stops short of 5 because it never distinguishes itself from adjacent siblings such as get_brand_perception, get_ai_competitors, or run_ai_visibility_audit.

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 phrase 'its tracked prompts' hints that prompts must already be configured (via set_tracked_questions/search_ai_prompts) before this is meaningful, but no prerequisite is stated. There is no explicit when-to-use or when-not-to-use, and no routing to the audit or competitor siblings.

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