suggest_domains_smart

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does well by detailing key behavioral traits: dual-source suggestions (semantic engine + GoDaddy AI), natural language understanding, auto-detection of industry, generation techniques (portmanteau, modern patterns), default filtering of premium domains, and pre-verified availability via GoDaddy. It lacks specifics on rate limits or error handling, but covers most operational aspects clearly.

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 appropriately sized and front-loaded, starting with a clear purpose statement followed by bullet-pointed features and examples. Every sentence adds value, though the bullet points could be slightly condensed. It efficiently communicates complex functionality without unnecessary fluff.

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, AI-powered features) and no annotations or output schema, the description does a good job of completeness. It explains the tool's behavior, features, and provides examples, covering most contextual needs. A minor gap is the lack of output format details (e.g., structure of returned suggestions), but overall it's sufficient for an agent to understand and use the tool effectively.

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 schema already documents all 6 parameters thoroughly. The description adds minimal parameter-specific semantics beyond the schema—it mentions 'industry' and 'style' in examples but doesn't elaborate on their effects beyond what the schema provides. This meets the baseline of 3 when schema coverage is high.

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 explicitly states the tool's purpose: 'AI-powered domain name suggestion engine' that 'Generate[s] creative, brandable domain names from keywords or business descriptions.' It clearly distinguishes from siblings like 'search_domain' (likely direct search) and 'suggest_domains' (likely simpler suggestions) by emphasizing its 'smart' AI-powered approach with dual sources and advanced features.

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 provides clear context for when to use this tool: for generating creative, brandable domain names from natural language queries, with examples showing different use cases. However, it does not explicitly state when not to use it or name specific alternatives among siblings (e.g., 'suggest_domains' vs. 'search_domain'), though the AI-powered features imply it's for more sophisticated suggestions.

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