search_ens_names

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

No annotations exist, so the description carries the burden. It clearly conveys read-only search behavior and states the output shape (name, price, owner, tags, availability). It doesn't mention rate limits or data freshness, but it goes beyond a bare 'search' statement.

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 front-loaded with the core purpose, then uses a scannable bullet list to enumerate query types. No redundant sentences; all content earns its place despite the length.

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?

With no output schema, the description explains what results contain and covers all major search categories. For a single-parameter tool, this is an impressively complete spec that leaves little ambiguity about expected behavior.

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 has 100% coverage for the single `query` parameter, so baseline is 3. The description adds valuable semantics by enumerating seven concrete query styles with examples, significantly enriching the meaning of what a query can contain.

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 states it searches ENS names using natural language, with a comprehensive list of query types (filtered, concept, creative, collection, activity, availability, bulk). This distinguishes it from narrower sibling tools like get_similar_names or check_availability by covering a broad natural-language search surface.

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?

Provides explicit examples of when to use it across multiple scenarios. It doesn't explicitly say when NOT to use sibling tools, but the query-type taxonomy implies it handles a wide range of user intents, making it the default entry point for natural-language search.

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