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

With no annotations, the description carries the full burden and does well: it discloses the cost model ('billed per input character'), the non-obvious default-model voice aliasing gotcha, and the return shape (status line plus audio content block with gateway mimeType). It does not mention auth requirements or rate limits, but the key behavioral surprises are covered.

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?

Front-loaded purpose sentence, then structured Args/Returns sections. The voice paragraph is the longest block but every clause is actionable (accepted names, aliasing behavior, workaround), so it earns its space.

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 no output schema, the description supplies the return format itself, plus cost and parameter guidance. For a two-parameter tool this is close to complete; only error/failure behavior and auth expectations are absent.

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 0%, so the description must compensate, and it does: it defines 'text' and gives substantial meaning for 'voice' beyond the schema — which named values are accepted, why they collapse to one voice on the default model, and concrete alternatives (Cherry/Ethan). This is real added value the schema lacks.

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?

Opens with a specific verb+resource ('Convert text to spoken audio') that is immediately distinguishable from siblings chat, generate_image, and list_models. No ambiguity about what the tool produces.

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 practical context — billing is per input character, and the voice paragraph tells the caller how to actually get a distinct voice. However, it never states when to use this tool versus the siblings (e.g. for audio output vs text), so the when-to-use dimension is only implied.

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