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

Annotations already indicate the tool is not read-only, not destructive, and can have open-world side effects. The description adds value beyond annotations by disclosing the cost (~$0.05), the character limit (1000), the model (ElevenLabs Turbo 2.5), and language support (32), giving the agent useful behavioral expectations for a paid, state-changing call.

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 a single, tightly packed sentence that front-loads the core purpose and includes essential operational details (format, model, languages, limit, cost). No filler or redundancy.

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 relatively simple tool with an output schema and clear annotations, the description covers the essential decision-making information: purpose, output format, constraints, and cost. It does not explicitly state when not to use it, but the description is otherwise complete enough for an agent to select and 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?

The schema already covers both parameters (text and voice) with descriptions, achieving 100% schema coverage. The tool description adds context such as the character limit, which indirectly informs the text parameter, but it does not substantially enhance the schema's parameter 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 tool's function with a specific verb and resource: 'Text-to-speech voiceover MP3'. It also provides distinctive details like the ElevenLabs model and language count, effectively distinguishing it from sibling tools such as ai_music and ai_image.

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 implies usage for text-to-speech tasks but does not explicitly state when to use this tool over alternatives, nor does it mention any exclusions or alternate tool recommendations. The context from sibling names suggests differentiation, but the description itself lacks explicit guidance.

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