speak

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

With no annotations, the description carries the full burden. It discloses the platform limitation and failure mode ('fails with an explanation elsewhere'), which is valuable. However, it does not explain the effect on the call (e.g., whether it interrupts, requires an active call, or is asynchronous), leaving behavioral uncertainty.

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?

Two short sentences, front-loaded with the action, no filler words. Perfectly concise.

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 4 parameters, no annotations, and no output schema, the description is too sparse to be fully complete. It omits parameter meanings and deeper behavioral context, making it adequate only for a very simple use case.

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 has 0% description coverage and the description provides no elaboration on parameters like voice, device, or session. It only implies that 'text' is the content to speak. The description does not compensate for the schema's lack of 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 ('Say') and resource ('something out loud into the call'), and the phrase 'out loud' differentiates it from text-based chat tools like chat_reply. It also adds a platform constraint. The only slight weakness is that 'something' is generic, but the intent is unambiguous.

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 provides a clear context (speaking aloud into a call) and an explicit when-not constraint (only local macOS installs, fails elsewhere). However, it does not name alternative tools or provide explicit comparison criteria, so it stops short of a 5.

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