generate_speech

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

With no annotations, the description must convey behavioral aspects. It discloses a dependency on the MCP server and mentions consent-based voice cloning, implying ethical constraints. However, it does not describe potential side effects, failure modes, or whether it is a read-only or mutating operation. The creation of audio is implied but not explicitly stated.

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 concise—three sentences efficiently cover purpose, key capabilities, and use cases. It is well-structured with a clear progression from general action to specific features and context, without superfluous details.

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 a single parameter, the description provides sufficient context: it states the action, the service used (ElevenLabs), the types of speech supported, and a prerequisite (MCP server connection). It omits explicit output details (e.g., audio file format) and alternative tool comparisons, but these are not critical for basic utilization. The description is reasonably complete.

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?

The input schema already describes the single parameter 'text' as 'Text to convert to speech,' providing 100% coverage. The tool description adds context about multilingual and emotional speech capabilities, which enriches the meaning of text, but it does not add concrete constraints such as length limits or formatting requirements. Thus, the description adds modest value beyond the 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 clearly states the tool's purpose with a specific verb ('Generate') and resource ('ElevenLabs models'), and lists use cases (multilingual narration, dialogue, emotional delivery) that differentiate it from sibling tools such as generate_image and generate_video.

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 implicitly suggests usage for speech and voiceover generation by listing scenarios like video narration and audiobooks, but it does not explicitly compare with alternative tools or state when not to use this tool. The dependency on the MCP server is noted, but no explicit selection guidance is provided.

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