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 valuable behavioral context: it probes each entity with ai_visibility_check, ranks by score, and returns a ranked list with detailed fields (score, confidence, signal density). This exceeds what annotations provide and ensures full transparency.

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, front-loaded with the core action, no fluff. Every sentence serves a purpose: stating what it does, how it works, and the output format. This is model conciseness.

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 4 parameters, no output schema, and annotations that cover safety, the description is remarkably complete: it describes the input (entities + optional params), the internal process (probes with ai_visibility_check), the output format (ranked list with score/confidence/signal density), and the use case. Nothing essential is omitted.

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 meaningful context beyond the schema: it explains that the first entity in 'entities' is treated as the 'subject' for narrative, and that 'context' disambiguates common names. This extra value justifies a 4.

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 specific verbs ('Compare', 'Probes', 'ranks', 'surfaces') and clearly identifies the resource (AI visibility across multiple entities). It explicitly distinguishes from siblings by stating it uses ai_visibility_check and targets competitive audits, making its purpose distinct from 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 clear context for use ('competitive AI-marketing audits') and implies when to use this over ai_visibility_check (for multi-entity comparison). However, it does not explicitly name alternatives or state when not to use it, stopping short of the 5-point bar.

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