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

Annotations only supply openWorldHint, so the description carries most of the burden and it does disclose the key behavioral trait: generation is asynchronous and returns a request ID rather than audio. It omits permission/auth requirements, latency expectations, and whether the request is durable, but the async contract is the critical disclosure.

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?

Three short sentences, front-loaded with the core action, then the mechanism, then the retrieval path. No filler or restated name/title padding.

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 usefully explains that the return value is a request ID and how to use it, closing the biggest gap an agent would face. It stops short of covering error behavior or the webhook-vs-poll choice, but is sufficient to invoke the tool 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 description coverage is 100%, so all six parameters (prompt, voice_id, model_id, webhook, track_id, temperature) are already documented in the schema. The description adds no syntax, format, or constraint details beyond what the schema provides, which is the expected baseline.

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 states a precise verb+resource: 'Convert text to natural speech audio,' and specifies the inputs that drive generation ('using the specified voice'). This is unambiguously distinct from the nearby speech-to-speech, speech-to-text, and text-to-video siblings.

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?

It gives clear workflow context by naming fetch-audio as the follow-up tool for retrieving results, which tells the agent this is an asynchronous submit step. It does not, however, explain when to prefer this over alternatives such as speech-to-speech or when a webhook should be used instead of polling.

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