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

Annotations already declare readOnlyHint=true and openWorldHint=true, and the description adds important behavioral context: it is a paid call, costs $7.00 USDC on Base via x402, and is not charged if the call fails. That payment and failure-charge behavior is valuable beyond the annotations.

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 description is compact and front-loaded: report scope first, then pricing and payment behavior. Every clause adds useful information with no filler.

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?

It covers the tool's purpose, scope, payment model, and failure-charge policy, which is important for a paid call. However, with no output schema and no description of what the report contains, an agent still lacks a clear picture of the returned artifact and why this deep tier should be chosen over siblings.

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 schema already documents all seven parameters well. The description adds only that this tier uses 50 prompts and all engines, which lightly clarifies the default scope but does not explain optional filters or how promptCount is capped by tier.

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 identifies a specific report resource and scope: AI brand visibility, deep report, 50 prompts, all engines. This distinguishes it reasonably well from ai_visibility_quick implicitly, though it does not explicitly name the sibling alternatives.

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 does not state when to use this tool versus ai_visibility, ai_visibility_quick, or serp_ai_monitor_deep. The word 'deep' and '50 prompts, all engines' imply a comprehensive use case, but there is no explicit routing guidance or exclusion criteria.

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