list_voices

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

The description casts this as a pure read ('Shows the language, gender and voice in use'), yet the annotations declare readOnlyHint=false, i.e. the tool is not read-only. That is a direct clash with the structured safety signal, and per the rubric a contradiction caps this dimension at 1.

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 sentences, front-loaded with what the tool returns, followed by the escape hatch for the larger catalog. Nothing is padded, though the second sentence is informational rather than about this tool's own invocation.

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 an output schema present, the description is not obliged to explain return values, and it correctly focuses on what is shown (language, gender, current voice, alternatives). For a zero-parameter listing tool this is essentially complete, modulo the unaddressed read-only mismatch.

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 tool takes no parameters, so there is nothing for the description to disambiguate; the empty object schema is self-explanatory. Baseline 4 for a zero-parameter tool.

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 ('Shows') and the exact content returned: current language, gender, active voice, plus the alternatives for the current language. That is enough to distinguish it from set_language at a glance, though the description never names a sibling explicitly.

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 draws the boundary between this tool and the fallback path: when the agent needs the full edge-tts catalog it is told to run `python -m edge_tts --list-voices` instead. Clear context for selection, but no explicit statement of when to prefer it over sibling tools like set_language or speak_summary.

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