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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint. The description adds value by disclosing that the tool probes each entity with ai_visibility_check, ranks by score, and returns a ranked list with score, confidence, and signal density. It does not contradict annotations and provides behavioral context beyond them.

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 two sentences with an embedded example, front-loading the primary purpose. Every sentence earns its place: the first defines functionality, the second explains the use case and return value. No filler or repetition of structured fields.

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?

The tool has moderate complexity (multiple entities, optional models, API key), but no output schema. The description compensates by stating the return format ('ranked list with score, confidence, signal density per entity'). It also names the underlying probe tool and explains the first-entity rule. Minor gaps: no mention of error handling or rate limits, but these are not critical for a read-only, idempotent tool.

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 the baseline is 3. The description adds important semantics for 'entities': 'First entry treated as the "subject" for narrative; rest are competitors.' This clarifies the interpretation of the first array element, which is not evident from the schema alone. It also provides a concrete example for the 'context' parameter.

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 purpose: comparing AI visibility across multiple entities side-by-side. It specifies the action (compare), resource (competitor AI presence), and behavior (probes with ai_visibility_check, ranks by score). This distinguishes it from sibling tools like ai_visibility_check (single entity) and compare_entities (general comparison).

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 explicit use cases: 'Useful for competitive AI-marketing audits' and an example query, 'does Claude know about us as well as our competitors?'. It implicitly differentiates from single-entity checks by emphasizing multiple entities, and clarifies that the first entity is the subject while the rest are competitors. This gives clear when-to-use guidance.

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