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

Beyond the read-only and open-world annotations, the description prominently discloses credit costs by size, free behavior for repeated empty lookups, the quote-before-confirmation flow for size 1000, and the returned total_count. This gives the agent the behavioral details needed to avoid surprise costs.

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 compact and well-structured: it front-loads the core result, then the pricing/quote behavior, then the return shape. Every sentence adds useful information with no redundancy or filler.

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 no output schema, the description provides everything an agent needs to invoke the tool correctly: required domain inputs, cost behavior, confirmation gate, limit default, and returned fields. It is a complete and self-contained definition.

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 coverage is 100%, and the schema already documents size cost tiers, limit default, and confirm_quote_id semantics. The description repeats and reinforces these details but does not add meaning beyond the schema.

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 is specific and actionable: it defines the tool as a link gap analysis that returns referring domains linking to a competitor but not to the user, ranked strongest first, with rank and link count. This clearly distinguishes it from sibling backlinks tools like backlinks_list or backlinks_referring_domains.

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 context is implicitly clear: an agent can infer this tool is for competitor gap analysis. However, the description does not explicitly say when not to use it or name any alternative sibling tool, so the agent must infer usage boundaries from the definition alone.

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