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

The description discloses that it 'Probes each entity with ai_visibility_check, ranks by score, surfaces which is most/least recognized' and 'Returns ranked list with score, confidence, signal density per entity.' This goes beyond the annotations (readOnly, openWorld, idempotent, destructive) by revealing the internal mechanism and return format. It does not mention rate limits or failure modes, but these are partially covered by the schema and annotations. No contradiction.

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 that are front-loaded with the core purpose, then process, then use case. There is no waste or repetition; every sentence adds value. It is appropriately sized for a composite tool.

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 params, 1 required, no output schema), the description is complete. It covers purpose, process, output shape, and a concrete use case. It also references ai_visibility_check, allowing the agent to understand the underlying primitive. The schema and annotations fill in remaining details.

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 does not add significant parameter-specific meaning beyond what the schema already provides; it mentions 'your brand + N competitors' but the schema already explains first entry as subject. No additional clarity is offered for models, _apiKey, or context.

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 the specific verb 'Compare' and clearly states the resource: 'AI visibility across multiple entities side-by-side.' It also describes the output (ranked list) and gives an example question, distinguishing it from siblings like ai_visibility_check (single entity) and compare_entities (general comparison). This is a clear, non-tautological statement of purpose.

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 mentions a use case ('competitive AI-marketing audits') and provides an example question ('does Claude know about us as well as our competitors?'). However, it does not explicitly exclude single-entity checks or name alternative tools (e.g., ai_visibility_check) for when to use them instead. Clear context but no exclusions.

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