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

Annotations are neutral (all hints false), so the description itself must disclose behavioral details. It does say that the tool 'returns audio' and that it supports batched execution, which is useful. However, it does not describe side effects, batching behavior semantics, or how `model_ids` changes output, so the disclosure remains somewhat surface-level.

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 description is two short sentences with no filler. The primary function is front-loaded, and the second line adds a meaningful implementation detail (bulk support). It is appropriately concise for the tool's purpose.

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 tool with 11 parameters and no output schema, this description gives the essential core operation and one important capability but does not fully explain optional controls or the actual response format beyond 'audio'. Given the rich JSON schema with enums, it is sufficient for simple usage but leaves advanced scenarios unanswered. It is a minimal-viable description rather than a high-context one.

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%, and the description compensates only partially by explaining that `inputs` is a list of text/voice ID pairs and that `model_ids` is for batch execution. It leaves most optional parameters (`settings`, `output_format`, `language_code`, `enable_logging`, `apply_text_normalization`, `pronunciation_dictionary_locators`) with no inline field-level meaning, but the schema's property names and enum values still offer moderate self-documentation.

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 clearly states the operation: 'Converts a list of text and voice ID pairs into speech (dialogue) and returns audio.' It names both the primary input and the output, and the 'Multi-Voice' label distinguishes it from single-voice TTS siblings. This is a specific verb+resource description, not a tautology.

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?

The description gives clear context for when to use it: when you have a list of text + voice ID pairs for multi-voice dialogue. It also explains a key capability: bulk execution via `model_ids`. It does not explicitly name alternatives or say 'do not use for single-voice speech', so it stops short of explicit alternate tool guidance.

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