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

Annotations already declare readOnly, openWorld, idempotent, non-destructive. The description adds behavioral detail: it probes each entity via 'ai_visibility_check', ranks results, and returns a ranked list with score, confidence, signal density per entity. It also notes the first entity is treated as 'subject'. No contradictions 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?

The description is three sentences, each earning its place: first sentence states the primary action and scope, second explains the process, third provides a concrete usage example with a quoted question. No superfluous information, front-loaded with the core function.

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 4 parameters and no output schema, the description adequately covers the workflow: it calls 'ai_visibility_check', ranks entities, and returns per-entity metrics (score, confidence, signal density). It lacks explicit detail on how scores are computed or what 'signal density' means, but still provides enough for an agent to understand the tool's output.

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 baseline is 3. The description clarifies that the first entity in the 'entities' array is treated as the 'subject' and mentions the optional '_apiKey' for Anthropic models. Beyond that, it does not add significant meaning beyond the schema descriptions, which are already clear.

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 uses specific verb 'Compare' and resource 'AI visibility across multiple entities side-by-side'. It clearly distinguishes from sibling 'ai_visibility_check' by emphasizing multi-entity comparison. States it probes each entity, ranks by score, surfaces most/least recognized, and provides a concrete use case ('competitive AI-marketing audits').

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 usage context ('competitive AI-marketing audits') and gives an example question. However, it does not explicitly state when not to use this tool versus alternatives like 'compare_entities', nor does it mention exclusions. The guidance is implied but not exhaustive.

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