list_tts_voicesList all available Brainiall Voice synthesis voices with metadata.
Returns: dict with keys: - voices (list): Available voices, each with id, name, gender, accent, grade - defaultVoice (str): Default voice ID
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the description's main burden is to explain the return contract. It does that clearly by specifying the 'voices' list fields and 'defaultVoice', which is useful context beyond the annotations.
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 compact and informative. The first sentence states the action and scope, and the return block adds necessary structural detail without redundancy or 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?
For a zero-parameter, read-only list tool, this description is complete: it names the resource, describes the output shape, and lists the key metadata fields per voice. No essential invocation or response-interpretation information 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?
With zero parameters, the description does not need to explain parameter meaning. The baseline of 4 applies because there is no parameter schema ambiguity to compensate for; the only relevant semantics are the return values, which the description covers.
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 states a specific verb ('List') and a specific resource ('all available Brainiall Voice synthesis voices'), which cleanly distinguishes it from sibling tools like synthesize_speech, voice_id_list_speakers, or transcription services. It also clarifies the output is metadata, not audio or other content.
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 tool's purpose strongly implies when to use it: when an agent needs the set of available TTS voices and the default voice ID. However, the description does not explicitly state when not to use it or mention an alternative, such as synthesize_speech when needing to actually generate audio.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools map to clearly distinct actions, but transcribe_audio and transcribe_audio_pro are near-duplicates and the four check_*_service tools require careful reading. The detailed descriptions make the distinctions recoverable, so confusion should be rare.
The set overwhelmingly follows a snake_case verb_* pattern, and the voice_id_* family is internally consistent. Minor deviations like get_phoneme_inventory vs list_tts_voices and the _pro suffix on transcribe_audio_pro keep it from being perfect.
Fourteen tools is within a reasonable range, but the server bundles pronunciation, STT, TTS, voice ID, and four health checks, making it feel broader than the 'Pronunciation' name suggests. A few health checks could be consolidated, but nothing is excessive.
Core pronunciation, transcription, and synthesis workflows are present, but the voice ID portion has create/list/verify/identify with no way to delete or unenroll a speaker. That is a notable lifecycle gap in an otherwise fairly complete speech toolkit.