set_language

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

Annotations already establish the safety profile (idempotent, non-destructive, not read-only), and the description consistently describes a settings mutation. It adds real behavioral context beyond the schema by specifying that an empty value preserves the current setting, i.e. partial-update semantics.

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 purpose and usage trigger are front-loaded in one sentence, followed by tight per-parameter notes. Every clause adds information; there is no filler.

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?

An output schema exists, so return values need not be described, and both parameters plus the safety annotations are covered. The only minor gap is scope/persistence (whether the change is global or per-conversation), which is only hinted at by 'per summary'.

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?

With 0% schema description coverage, the description carries the full burden and does so well: it defines the accepted values for language (ISO codes, 'system', 'auto') and gender ('f'/'m', 'any'), plus the empty-string keep-current behavior for both. This is exactly the compensation needed when the schema is bare.

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 ('Changes') and resource ('the voice language and gender'), so the agent knows exactly what is being modified. It does not explicitly distinguish itself from siblings like list_voices or speak_summary, but the effect is unambiguous.

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 a clear triggering condition: 'for when the user asks to speak another language or use a different voice.' This tells the agent when to reach for this tool, though it names no alternatives or exclusions relative to its siblings.

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