voice_id_list_speakersList the speakers enrolled in a group.
Returns: dict with keys: speakers (list of {speaker_id, n_samples, ...}).
| Name | Required | Description | Default |
|---|---|---|---|
| group_id | Yes | The group/namespace to list |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish readOnlyHint, idempotentHint, openWorldHint, and non-destructive behavior, so the description need not repeat those. It adds the return shape but does not disclose edge-case behavior such as whether a nonexistent group returns an empty list or an error; still, annotations carry most of the safety burden.
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 very short, front-loaded with the action, and uses a clear return contract. Every sentence earns its place with no redundancy.
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 single-parameter, read-only list operation with rich annotations, the description is largely complete and even includes the return shape because no output schema exists. It could be slightly stronger by stating whether an unknown or empty group returns an empty speakers list, but this is a minor gap.
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 coverage is 100%, and the group_id description ('The group/namespace to list') fully explains the parameter. The description's mention of 'a group' adds no new semantic detail beyond the schema, so the baseline of 3 applies.
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 uses a specific verb ('List') and resource ('speakers enrolled in a group'), making the operation unambiguous. It is clearly differentiated from voice_id_enroll, voice_id_identify, and voice_id_verify, and from list_tts_voices by the domain (speaker enrollment vs TTS 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?
The description clearly indicates when to use the tool: whenever an agent needs to list enrolled speakers for a specific group. It does not explicitly name alternatives or exclusions, but the sibling tool set makes the appropriate context obvious.
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.