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

The description goes beyond the readOnly/idempotent hints by disclosing that it 'Probes each entity with ai_visibility_check, ranks by score, surfaces which is most/least recognized' and returns 'score, confidence, signal density per entity.' This adds orchestration and output behavior not present in annotations. No contradiction detected.

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 front-loaded with the core purpose, followed by behavior, use-case, and return details. Each sentence contributes value and the length is appropriate for a 4-parameter tool with no output schema. It is not overly terse or verbose.

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 orchestrates multiple probes and has no output schema, the description adequately covers what it does, how it works, when to use it, and what it returns. It does not explain edge cases like fewer than two entities or API failures, but the schema already specifies the 2-8 constraint, so this is reasonably complete.

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?

The input schema already provides 100% coverage with detailed parameter descriptions for models, _apiKey, context, and entities. The description adds only a light conceptual framing (e.g., 'your brand + N competitors') but does not materially improve understanding beyond the schema, so the baseline of 3 is appropriate.

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 opens with a specific action: 'Compare AI visibility across multiple entities side-by-side.' It clearly distinguishes itself from the sibling ai_visibility_check by focusing on multi-entity comparison and ranking, and from generic compare_entities by framing it as a competitive AI-marketing audit tool.

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?

Provides clear context: 'Useful for competitive AI-marketing audits' and explicitly illustrates the question, 'does Claude know about us as well as our competitors?' It implies a multi-entity scenario but does not explicitly state when to prefer this over ai_visibility_check or compare_entities, nor does it list exclusions.

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