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transcribe_selection

Transcribe only the currently selected audio region in Audacity. Runs in the background and returns a job ID, with language auto-detection or explicit language and translation options available.

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.

Language auto-detection can occasionally misidentify the language on a short or ambiguous clip. If you already know the audio's language, pass language explicitly (e.g. "en"), or set task="translate" to force English output.

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
Behavior5/5

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

No annotations, but description fully discloses experimental status, background execution returning a job_id, and the language auto-detection limitation. Also notes setup requirement.

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?

Structured with functional headings and concise paragraphs; every sentence adds value (prerequisite, async behavior, language caution).

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

Completeness5/5

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

Covers setup, prerequisite, return behavior, monitoring, and language handling. No output schema, but the description provides sufficient context for invocation and response expectations.

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

Parameters5/5

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

Schema has zero descriptions, but the description's Args section fully documents model_size values, language as ISO or None, and task options, adding all necessary meaning.

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?

States 'Transcribe only the currently selected audio region' – a specific verb and object that distinguishes it from sibling transcription tools like transcribe_audio.

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?

Gives clear prerequisite ('Select a region first') and monitoring instructions ('Use check_transcription_status'). Does not explicitly list alternatives or when-not-to-use, but the scoped wording implies the use case.

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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