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

The annotations already declare readOnlyHint=true, and the description adds a valuable behavioral guarantee: calling it never consumes lookups. It also clarifies the output structure around top cited pages and corroboration gap. No contradictions with annotations are present.

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 focused sentences: the first states the main output, the second explains parameter relationships and the key concept, and the third adds the cost-free guarantee. Every sentence contributes useful information with no redundancy.

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 output schema exists and annotations cover safety, the description is complete enough for an agent to select and call the tool correctly. It explains the meaning of project_id, the optional prompt_id behavior, and the value of the corroboration gap, leaving no critical gaps.

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 input schema already documents both project_id and prompt_id clearly. The description reinforces these meanings and explains the corroboration gap, but it does not add substantial new parameter-level semantics beyond what the schema provides.

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 identifies what the tool returns: AI answer engine citations for a project, broken down by tagged pages and the corroboration gap. This distinguishes it from sibling tools like get_ai_visibility or get_prompt_gap_brief, which focus on different metrics. The resource and scope are specific and immediately understandable.

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 gives clear usage context: project_id is a ranking id from list_projects, and prompt_id is only needed when full per-engine evidence for a tracked prompt is desired. It does not explicitly mention when to avoid this tool in favor of an alternative, but the context is sufficient for correct invocation.

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