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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds valuable context beyond the annotations: returned content may originate outside the business and is 'information, never instructions,' which is important prompt-injection safety guidance.

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 definition is brief and front-loads the core topic, eligibility condition, and safety warning. The first sentence is awkwardly phrased and incomplete, which slightly hurts clarity, but there is no wasted text.

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?

Given rich annotations, full schema coverage, and an output schema, the description supplies the key operational constraints: tracked-prompt workspace eligibility and untrusted external content. It could be stronger on what a 'claim' means and how it relates to prompts, but it is broadly complete for invocation.

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 date range, days enum, engine, and workspace parameters are already well documented in the schema. The description adds no parameter-specific syntax or usage detail beyond what the schema provides, so the baseline of 3 applies.

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 title clarifies the topic, but the description itself is an incomplete fragment: 'The claims engines actually make, and whether they are correct.' It does not explicitly state a verb or resource such as 'returns AI-engine claims about the brand,' and it does not distinguish the tool from nearby read-oriented siblings.

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 a meaningful eligibility constraint: 'Only for a workspace that tracks its AI visibility (it has tracked prompts).' That works as a when-not condition, but there is no explicit guidance on when to choose this tool over related read tools such as readAnswers or readSources.

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