check_whisper_serviceCheck if the Brainiall Speech Pro service is healthy and ready.
Returns: dict with keys: - status (str): 'healthy' or error state - modelLoaded (bool): Whether the Brainiall Speech Pro engine is loaded - diarizeLoaded (bool): Whether the diarization pipeline is loaded - version (str): API version - modelName (str): Engine version identifier
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is established. The description adds useful context about what 'healthy and ready' means via the returned fields, but does not go deeper into operational behavior such as startup requirements, error triggers, or rate limits.
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 purpose is front-loaded in one sentence, and the return contract is listed compactly in a structured block. There is no filler, though the return-key list is a bit mechanical and could have been tightened further.
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 health check with strong annotations and no output schema, the description provides the essential return contract and states the tool's purpose. Minor omissions like the exact meaning of an error state and the relationship to the Whisper subservice do not prevent correct invocation.
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 has zero parameters, so the description rightfully contains no parameter details. With no params, the baseline is 4, and there is nothing more the description needs to explain.
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 ('check') and names a concrete resource ('Brainiall Speech Pro service'), with return keys clarifying what is checked. However, it does not explicitly distinguish itself from sibling health-check tools like check_tts_service or check_pronunciation_service, and the 'Brainiall Speech Pro' label is not obviously connected to the 'whisper' tool name.
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?
There is no guidance on when to use this tool versus sibling health checks. The purpose implies use before dependent speech operations, but the description never states when to prefer this tool, what prerequisites exist, or which alternatives to consider.
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.