recommend_domain

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

With no annotations, the description carries the burden of behavioral disclosure. It reveals that suggestions are 'creative name + TLD combos with a category', 'cross-checked for availability', 'priced', and 'given a register link'. This clearly explains what the user receives and the processing involved, though it does not detail edge cases or potential limitations.

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 primary purpose, and contains no filler. Every word adds value, from the specific examples to the output features.

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?

Despite lacking an output schema, the description summarizes the return content (name+TLD, category, availability, price, register link), which is essential for the agent to understand what to expect. It also covers usage scenarios. Minor gaps like error handling or pagination details are acceptable for a recommendation tool, but prevent a perfect score.

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 input schema has 100% coverage, so a baseline of 3 applies. The description adds value by providing concrete examples for the 'query' parameter (e.g., 'tom', 'crypto', 'defi') and hinting at the 'tlds' parameter through the '.xrp ideas' example, enriching the semantic understanding beyond the schema's basic descriptions.

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 purpose: 'Get AI-recommended domain suggestions for a keyword or theme.' It specifies the resource (domain suggestions) and the action (recommend), and distinguishes it from siblings like check_domains and register_domain by focusing on AI-based recommendations rather than checking or registering.

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 explicit when-to-use triggers: 'Use when a user asks "suggest names", "find me a domain about X", or "give me some .xrp ideas".' It does not explicitly mention when not to use or name alternative tools, but the usage guidance is clear and actionable, earning a 4 rather than a 5.

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