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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is clear. The description adds value by explaining the tool probes each entity with ai_visibility_check, ranks by score, and returns score, confidence, and signal density. No contradiction with 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?

Three sentences, each earning its place: purpose, method, use case + output. No unnecessary words, front-loaded with the core action.

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?

Despite no output schema, the description specifies the return format (ranked list with score, confidence, signal density). All 4 parameters are covered, and the tool's purpose is fully explained. No gaps for the complexity level.

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 each parameter has a description. The description adds extra context: entities must be 2-8 with first as subject, models explanation, and optional context for disambiguation. This exceeds baseline 3 by providing ordering and limits, improving the agent's understanding.

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?

Description clearly states the tool compares AI visibility across multiple entities side-by-side, distinguishes from sibling ai_visibility_check which probes a single entity, and gives a concrete use case (competitive AI-marketing audit). Verb 'compare' plus specific resource 'AI visibility across multiple entities'.

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?

Description explicitly frames the tool for competitive audits and provides a concrete example ('does Claude know about us as well as our competitors?'). While it doesn't explicitly state when not to use it or name alternatives, the context of sibling ai_visibility_check implies single-entity usage, but this is not explicit in the description. Score 4 because it gives clear context but lacks explicit exclusions.

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