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

Annotations already declare the tool as read-only, idempotent, non-destructive, and open-world. The description adds useful behavioral context: up to 10 questions, latest check results, last 7 checks, and competitor naming details. It does not discuss freshness beyond 'latest' or truncation behavior, so it is strong but not exhaustive.

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 purpose and avoids filler. The first sentence is dense with enumerated result categories, but every part contributes useful scoping detail.

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 an output schema, rich annotations, and a fully described single parameter, the description is complete enough for an agent to select and invoke the tool correctly. It covers scope, constraints, use cases, and the key alternative.

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%, and the site parameter is fully documented in the schema. The description does not add parameter-specific meaning beyond what the schema provides, so the baseline of 3 applies.

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 specifies the exact resource and scope: one site's questions, latest AI check results, last 7 checks, and competitors named. It also clearly distinguishes the tool from ai_answer, which handles exact AI wording.

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?

It gives concrete example questions that map directly to use cases and explicitly routes the agent to ai_answer when exact AI wording is needed. This is clear when-to-use and alternative guidance.

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