List text-to-speech voices

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

Annotations already declare readOnlyHint, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered elsewhere. The description itself adds no behavioral context such as filtering scope, deprecation handling, or pagination behavior, so it contributes almost nothing on this dimension.

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?

A single front-loaded sentence with no filler or redundancy. It is efficient, though arguably so terse that it leaves room for a little more useful scope detail.

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 an output schema present and annotations covering the safety profile, the description does not need to explain return values. It is minimally adequate for a simple list tool, but omits filtering/pagination cues that would round out the picture.

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% with four well-documented parameters (limit, query, cursor, includeDeprecatedVoices), so the schema already carries parameter meaning. The description adds no additional parameter semantics, which is the expected baseline 3 when the schema does the work.

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 pairs a specific verb (List) with a specific resource (text-to-speech voices) and names the consuming features (narration, text_to_speech, workflows). It is distinct from siblings like list_languages or list_files, though it doesn't explicitly contrast itself with any of them.

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?

Mentioning narration/text_to_speech/workflows implies when an agent would want voices, but there is no explicit when-to-use or when-not-to-use guidance and no named alternative tool. Usage is only weakly implied.

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