list_voice_models

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

Annotations already declare readOnlyHint/idempotent/destructive, so the safety profile is covered; the description adds a genuinely non-structured fact — that the call does NOT consume credits, which matters for cost-aware agents. It does not describe the shape of the returned model list, which remains a minor gap for a tool with no output schema.

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?

Two tight sentences: purpose plus examples first, then the downstream usage instruction and cost note. No filler and nothing buried.

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 one-parameter, read-only lookup with full schema coverage and rich annotations, the description covers what it returns conceptually (modelIds) and how to use them. Only the exact return fields are unspecified, which is a small gap given no output schema exists.

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 single parameter is fully documented in the schema (100% coverage) with provider slugs enumerated, so the description need not repeat syntax. The description's examples are model IDs rather than provider slugs, so it illustrates the output rather than adding parameter meaning beyond the schema. Baseline 3 applies.

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?

States a specific verb (list) and resource (TTS models) scoped to a provider, with concrete example model IDs per vendor. It is clearly distinguishable from list_voice_providers and search_voices / list_provider_voices, which it names as downstream consumers.

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?

Explicitly says to feed the returned modelId values into search_voices / list_provider_voices, which gives the agent a clear place in the workflow. It lacks an explicit 'do not use this if you want X' exclusion versus list_voice_providers, but the sequencing guidance is strong.

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