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YuvrajSinghBhadoria2

OpenCode Voice MCP Server

voice_transcribe

Capture microphone audio and convert speech to text. Provides transcribed text for voice input in AI coding tools.

Instructions

Record audio from microphone and transcribe to text. Returns the transcribed text.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
durationNoRecording duration in seconds (default: 10)
languageNoLanguage code for transcription (e.g., 'en', 'es', 'fr'). Default: auto-detect
Behavior2/5

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

No annotations are provided, so the description must carry the transparency burden. It discloses only the primary behavior (recording and transcribing) but omits any prerequisites, such as microphone permissions, whether audio is stored, error handling, or potential side effects. This is a significant gap for a tool that records audio.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, consisting of two short sentences: 'Record audio from microphone and transcribe to text. Returns the transcribed text.' No unnecessary information is included, and the main action is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has only two optional parameters and no output schema, so the description is mostly adequate. However, it lacks additional context that would be valuable, such as recording duration defaults, language auto-detection behavior, or any limitations. The schema covers parameter details, but the description remains minimal for a tool with no annotations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema provides descriptions for both parameters (duration and language), achieving 100% schema description coverage. The description adds no additional meaning about these parameters or their behavior, so the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action: 'Record audio from microphone and transcribe to text.' It specifies the verb (record/transcribe), resource (microphone), and output (text). This distinguishes it from sibling tools 'voice_status' and 'voice_type', which likely handle different voice-related functions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies a clear usage context: when you need audio transcribed. It does not explicitly mention alternatives or exclusions, but the action is straightforward enough that the use case is evident. Since it says 'Record audio from microphone and transcribe to text,' there is no ambiguity about when to use it.

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

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