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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds behavioral context: it probes each entity with ai_visibility_check, ranks results, and surfaces the most/least recognized. This enriches the agent's understanding beyond annotations without 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?

Two sentences, each earning its place. First sentence captures core purpose, second elaborates on method, use case, and output. No wasted words; front-loaded with key action.

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?

For a multi-entity comparison tool with inner tool calls and no output schema, the description adequately covers input semantics, process (using ai_visibility_check), and output format (ranked list with score, confidence, signal density). It does not address edge cases or error handling, but given the annotations (read-only, idempotent), this is acceptable.

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 adds valuable semantic information beyond the schema: for 'entities', it states 'First entry treated as the 'subject' for narrative; rest are competitors.' This clarifies the role of the first entity, which is not in the schema description.

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 'Compare AI visibility across multiple entities side-by-side', specifying the verb 'compare', the resource 'AI visibility', and the scope 'multiple entities'. It distinguishes from siblings like ai_visibility_check (single entity) and compare_entities (generic) by focusing on AI visibility ranking.

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 a concrete use case: 'competitive AI-marketing audits' with an example question. While it does not explicitly exclude alternatives, the description implies when to use this tool over others (e.g., for multi-entity AI visibility comparison). Lacks explicit 'when not to use' guidance.

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