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

With no annotations, the description carries the burden of disclosing behavior. It states that the tool generates names, checks availability, and returns only available domains with pricing. This is honest and useful, though it doesn't mention potential side effects, cost to the user for invoking the tool, or limitations like asynchronous availability checking. Yet, for a suggestion tool, the key behavioral facts are disclosed.

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 two sentences, front-loaded with the core purpose ('AI-powered domain suggestions'), and includes a concrete example. Every sentence contributes meaning, and there is no fluff or 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 tool's moderate complexity (6 parameters, no output schema), the description covers the essential behavior: input, generation, availability filtering, and pricing output. It also includes an illustrative example. However, it doesn't clarify the exact return structure or how availability/pricing is determined, which would benefit from a bit more detail, but the schema covers parameter syntactics, so this is sufficient for correct use.

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 minimal parameter-specific meaning beyond the schema: it mentions 'creative TLDs' (echoing the tlds parameter) and 'project description' (prompt). Since the schema already thoroughly documents all six parameters with descriptions and enums, the description is not required to compensate.

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 states the tool's function: AI-powered domain suggestions based on a project description, generating full domain names with creative TLDs and returning only available ones with pricing. It uses specific verbs and distinguishes itself from sibling tools like buy_domain or search by emphasizing the suggestion/generation aspect.

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 implies the appropriate use case: when a user needs domain name ideas from a project description. It mentions the input (project description) and specific behavior (checks availability, returns pricing), making the context clear. However, it doesn't explicitly contrast with alternatives like browse_marketplace or search, so it stops short of full exclusion guidance.

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