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

Annotations already indicate idempotent, read-only, non-destructive behavior. The description adds behavioral details: it probes each entity using 'ai_visibility_check', ranks results by score, and surfaces most/least recognized. This adds value without contradicting 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?

Two sentences with zero wasted words. The main action is front-loaded, followed by a brief explanation of process and a concrete use-case example. Every sentence earns its place.

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?

There is no output schema, but the description explicitly states returns: 'ranked list with score, confidence, signal density per entity'. It covers parameter roles and the tool's purpose sufficiently for a multi-entity comparison tool with clear annotations.

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 coverage is 100%, so the baseline is 3. The description adds semantic value by stating that the first entity in 'entities' is treated as the 'subject' and the rest as competitors, which is not captured in the schema. This provides actionable guidance beyond the schema's descriptions.

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 the tool's action ('Compare AI visibility across multiple entities side-by-side') and specific resource ('AI presence'). It also distinguishes itself from sibling tools like 'ai_visibility_check' and 'compare_entities' by emphasizing multi-entity comparative ranking.

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 explicitly situates the tool's usage in competitive AI-marketing audits and provides a concrete use-case question. It implies when not to use (if only a single entity is needed) and mentions that the first entity is treated as the 'subject' for narrative, guiding the agent on parameter ordering.

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