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transcribe_selection

Transcribe the currently selected audio region using Whisper models. Runs in background and returns a job ID to monitor progress.

Instructions

[EXPERIMENTAL] Transcribe only the currently selected audio region. Requires separate setup — see installation guide.

Runs in BACKGROUND — returns a job_id immediately. Use check_transcription_status to monitor progress.

Select a region first, then call this tool.

Args: model_size: Whisper model - "tiny", "base", "small", "medium", "large-v3" language: ISO language code or None for auto-detect task: "transcribe" or "translate"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskNotranscribe
languageNo
model_sizeNosmall
Behavior3/5

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

No annotations provided, so description carries full burden. Discloses experimental status, background execution, and job_id return. Does not address side effects, permissions, or limitations like max selection length. Adequate but not comprehensive.

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?

Concise, front-loaded with main purpose, no fluff. Parameter list is structured and clear. Every sentence adds value.

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

Completeness4/5

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

Given no output schema and background execution, description covers workflow (selection, call, status check). Lacks details on output format or constraints, but overall sufficient for a single-purpose tool with a clear sibling for follow-up.

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

Parameters4/5

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

Schema coverage is 0%, but description adds meaningful explanations for all three parameters (model_size, language, task) with examples and defaults, compensating well for the lack of schema descriptions.

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?

Clearly states 'Transcribe only the currently selected audio region', specifying verb 'Transcribe' and resource 'selected audio region'. Distinguishes from siblings like transcribe_audio (presumably for full track) and transcribe_to_labels/file.

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?

Provides explicit steps: 'Select a region first, then call this tool', mentions background execution and use of check_transcription_status for monitoring. Lacks explicit alternatives for when-not-to-use, but context of siblings implies scope.

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

Install Server

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