List text-to-speech engines

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds behavioral context beyond that: it explains the list is derived by filtering ha.get_states() for `tts.` prefixes, which tells the agent the source of data and scope of results.

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?

Front-loaded with the core purpose, then organized into terse Use-when / Not-for / Returns clauses. Every sentence adds routing or behavioral value with no filler.

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?

Given zero params, rich annotations, and an existing output schema, the description covers everything an agent needs: what it lists, when to use it, which siblings to avoid, and the shape of the result. Nothing material is missing.

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 zero parameters, so there is nothing for the description to disambiguate; the empty schema is self-explanatory. Baseline of 4 applies for a no-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 (List) and resource (text-to-speech engines) and pins down exactly what is returned ('as their `tts.*` entities'). It distinguishes itself from the nearby voice_list_stt_engines and voice_list_wake_word_engines siblings by name, so an agent can route without opening any schema.

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?

Contains explicit 'Use when' and 'Not for' clauses, and names the alternative sibling tools for the disallowed STT/wake-word cases. The selecting condition (discovering a TTS entity ID to pass to voice_create_pipeline/voice_update_pipeline) is spelled out.

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