Synthesize speech

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

No annotations are provided, so the description carries the full behavioral burden. It discloses determinism (same text/voice/seed gives same audio), format-specific container quirks (random stream serial for ogg/opus), speed behavior with pitch preservation, continuation semantics, truncation detection, and a detailed error structure with `error_kind`, `supported`/`available`, and `code`. This is exemplary transparency.

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?

Although long, every sentence earns its place. The description leads with the core action and return value, then systematically covers formats, determinism, language, speed, continuation, truncation, and errors. There is no redundancy or fluff; the structure is logical and front-loaded with the most important facts.

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?

Given the tool's complexity (7 parameters, multiple formats, error cases, continuation), and the absence of any annotations, the description is remarkably complete. It explains what is returned, how parameters affect behavior, how to chain calls, and how to interpret errors. An output schema exists, so the return structure is likely further defined, but the description covers everything an agent needs to call it correctly.

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 coverage is 0%, so the description must explain every parameter. It does: `format` with defaults and size trade-offs, `language` with default behavior, `speed` with range and pitch preservation, `previous_tokens` with its continuation purpose, and `seed` via the determinism statement. `text` and `voice` are self-evident but still implied. The description adds meaning beyond the bare schema.

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 opens with a crisp verb+object pair ('Turn text into speech in a named voice') and then specifies the exact resource and the output shape (base64 audio, duration, token count). It clearly distinguishes itself from the siblings (list_voices, describe) by focusing on synthesis rather than enumeration or inspection.

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 explicit when-to-use guidance for each format ('worth asking for when the reply is saved to a file rather than played', 'for a reply sent on to a chat or a phone'), explains when to omit or pass `language`, and describes the continuation mechanism for long texts. It even tells the caller to check `truncated` to detect cut-off speech. This is proactive, alternative-aware guidance.

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