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

With no annotations, the description still discloses the payload (voice names plus descriptions) and the operational sequencing relative to text_to_speech, so the agent knows this is a cheap read used for discovery. It does not say whether the list is static, whether it can fail, or what the notification_message parameter does on failure, which keeps it short of a 5.

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 tight sentences front-load the purpose and routing rule. The trailing enumeration of 16 voice names is the only questionable content: it duplicates what the tool returns and could go stale, though it lets the agent answer basic questions without a call.

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?

There is no output schema, so the description correctly carries the return shape (names and descriptions) — that burden is met. For a zero-required-parameter read tool with no annotations, the remaining gaps (failure behavior, list freshness) are minor.

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% and the single parameter (notification_message) is fully documented in the schema, so the baseline is 3. The description adds nothing about that parameter — notably it does not explain how a fallback notification relates to a list operation — but there is no gap to compensate for.

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?

States a specific verb and resource ("List all available YarnGPT voices") and immediately says what the result contains (names and descriptions). It is clearly distinguishable from the only sibling, text_to_speech, which synthesizes speech rather than enumerating voices.

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?

Explicit routing: "Use before text_to_speech when the user asks which voices exist or which voice to pick." It names the alternative tool and the exact user intents that select this one, leaving nothing to inference.

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