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

Discloses important data-quality caveats beyond the annotations: traffic estimates, legacy snapshots, non-canonical page titles, correlation-only AI signals, missing rank behavior, and quota consumption. These are exactly the non-obvious behaviors an agent needs to interpret results correctly.

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 dense and long, but nearly every sentence carries a distinct warning or clarification that prevents misuse. The core purpose is front-loaded, and the additional caveats are organized around the returned fields rather than random trivia.

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, the description focuses on field semantics, entity-type caveats, quota cost, and the follow-up save action. It covers the important interpretation pitfalls and operational constraints without needing to restate the full return shape.

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?

The schema already describes the domain parameter well, and the description adds context about domain surfaces and the correct ID for saving. However, the added value over the schema is moderate; most parameter meaning comes from the schema itself.

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?

Clearly identifies the action ('Fetch') and resource ('one domain surface's FULL profile') with a specific domain parameter. The description also clarifies what the profile does and does not represent, which prevents misclassification of the entity.

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?

Gives clear context: use it to fetch a single domain surface, and explicitly redirects saving to add_to_favorites with the correct entity type and parameter shape. It also tells the agent to inspect registrable_domain and domain surface type to avoid misreading the entity, though it does not contrast directly with the sibling search tools.

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