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

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds valuable behavioral details: 'Probes each entity... with ai_visibility_check, ranks by score, surfaces which is most/least recognized.' It also reveals the output structure (ranked list with score, confidence, signal density), which is absent from the output schema. No contradictions.

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 three sentences with no redundancy. First sentence states purpose, second explains mechanism, third provides use case and output format. Every sentence contributes essential information.

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 the tool's moderate complexity (4 parameters, 1 required), the description fully covers purpose, mechanism, usage context, and return format. It explains how the tool works (calls ai_visibility_check for each entity and ranks), what to expect as output, and when to use it. No gaps remain.

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%, baseline 3. The description adds value by explaining that the first entity in 'entities' is treated as the 'subject' for narrative, which is not in the schema. It also clarifies the ranking and output format. However, it does not add significant new insights for other parameters beyond the schema.

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 clearly states it 'compare[s] AI visibility across multiple entities side-by-side.' It specifies the verb 'compare' and resource 'AI visibility across entities', distinguishing it from sibling tools like ai_visibility_check and compare_entities by explaining it probes multiple entities and ranks them.

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?

The description provides clear context: 'Useful for competitive AI-marketing audits' with a concrete example. It implies when to use (comparing multiple entities) and hints at when not to (use ai_visibility_check for single entities) but doesn't explicitly exclude alternatives.

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