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

With no annotations, the description carries the full burden. It clearly states the tool returns classification and common usage ('curated metadata'), which is transparent for a simple lookup. However, it does not disclose edge cases (e.g., missing TLDs), data source, or error behavior, leaving some behavioral aspects implicit.

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 concise and well-structured: a one-sentence purpose followed by clear 'Use when' and 'Do not use when' bullet points. Every sentence earns its place, and the front-loaded purpose ensures quick comprehension.

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?

For a simple one-parameter lookup tool with no output schema, the description covers the essentials: purpose, usage context, exclusions, and a hint of return value ('classified as and commonly used for'). It is adequately complete, though a bit more detail on return format would push it to 5.

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 schema has 0% description coverage, but the description compensates by explaining the parameter through examples ('com', 'io', 'ai') and clarifying that it takes a TLD without a leading dot. The parameter name 'tld' is self-explanatory, and the description adds usage context 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 opens with a specific verb ('Identify') and resource ('DNS top-level domain'), clearly stating the tool classifies TLDs and describes their common usage. It distinguishes itself with concrete examples (com, io, ai) and is clearly distinct from sibling tools like mime_lookup.

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 'Use when' section provides explicit example queries ('What kind of TLD is .io?', 'Is .ai a country-code or generic top-level domain?'), and the 'Do not use when' section lists exclusions with an explicit alternative for MIME types (mime_lookup). This fully satisfies the dimension.

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