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

Annotations declare readOnlyHint, idempotentHint, destructiveHint; description adds that it probes each entity with ai_visibility_check, ranks results, and returns score/confidence/signal density. No contradictions. The description provides useful behavioral context beyond the 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 a single paragraph of 3-4 sentences, front-loaded with the main purpose. Every sentence adds value without repetition or fluff.

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 explains the return format (ranked list with score, confidence, signal density). It describes the internal process (calling ai_visibility_check) and the input contract (2-8 entities, etc.). The tool is complex but the description covers all key aspects.

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 baseline is 3. The description adds some context (first entity treated as subject, role of context) but does not significantly enhance parameter understanding beyond the schema 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 uses a specific verb-resource pair 'Compare AI visibility' and clearly distinguishes from sibling tool 'ai_visibility_check' by emphasizing multi-entity side-by-side comparison. It explicitly states what the tool does and its competitive audit use case.

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 states when to use: for competitive AI-marketing audits, with an example. It contrasts with the single-entity sibling 'ai_visibility_check' by mentioning 'probes each entity... ranks by score'. Lacks an explicit 'when not to use' statement but is otherwise clear.

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