list_models

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

With no annotations provided, the description carries the full disclosure burden; '一覧を返す' implies a side-effect-free read, but this is never stated outright. It also does not mention result volume, whether models depend on authentication or subscription tier, or any caching/staleness behavior, though the existence of an output schema reduces the need to describe the return shape.

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 compact sentence with the verb and the enumerated contents front-loaded, and no filler. The enumeration of four content categories is slightly list-like but each item is informative.

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 zero-parameter listing tool with an output schema, the description covers what is returned and needs to say little else. The one meaningful gap is the lack of differentiation from the sibling list_voices, which returns voices and could confuse tool selection.

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 tool takes zero parameters, so there is nothing for the description to clarify at the parameter level; the baseline for a no-parameter tool applies. The description correctly implies the call is unfiltered and takes no arguments.

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 has a clear verb ('一覧を返す' — returns a list) and enumerates the resources covered: TTS models, aliases, prebuilt voices, and output settings. It does not, however, distinguish this tool from the sibling list_voices, even though it claims to also return prebuilt voices, leaving overlap for the agent to resolve.

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?

Usage is only implied: the agent can infer this is a discovery/introspection call for available models and settings. There is no explicit statement of when to call it versus list_voices or auth_status, and no prerequisites or exclusions are given.

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