check_stt_serviceCheck if the Brainiall Speech service is healthy and ready.
Returns: dict with keys: - status (str): 'healthy' or error state - modelLoaded (bool): Whether the speech-recognition model is loaded - version (str): API version
| 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, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context by documenting the return keys including status, modelLoaded, and version, which clarifies what 'healthy and ready' means operationally.
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 front-loaded with the core purpose, followed by a concise structured return-value breakdown. Every sentence contributes necessary information 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 health check, the description adequately covers the return values and the meaning of readiness. It does not discuss potential error states in detail or clarify differences from sibling health-check tools, but the simple scope makes the current description reasonably complete.
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 and the schema is empty, so there is no parameter burden on the description. The baseline of 4 applies because parameter semantics are not applicable and nothing is missing.
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 clearly states the verb 'Check' and the resource 'Brainiall Speech service', and specifies what 'healthy and ready' means through the returned keys. It does not explicitly distinguish itself from sibling health-check tools like check_tts_service or check_whisper_service, so it stops short of full differentiation.
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 implies this is a health/readiness check to perform before using STT functionality, but it does not explicitly state when to use this tool versus the sibling check_pronunciation_service, check_tts_service, or check_whisper_service. No exclusions or alternative routing are provided.
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.