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transcribe_audio

Transcribe speech from an audio or video file (unbilled draft).

    Use the returned segments with `translate` (origin via text) then
    `synthesize_audio` to produce a dubbed track. Video uploads also
    return a video_id for muxing.

    Args:
        file_path: Public HTTPS URL (hosted) or local path (stdio) to audio (mp3, wav, m4a, …) or video (mp4, mov, …).
        source_language_code: Optional source language hint (e.g. "en").
        keep_background_music: If true, split a music bed for later remix.
    

Input Schema

NameRequiredDescriptionDefault
file_pathYes
source_language_codeNo
keep_background_musicNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

No annotations exist, so the description carries the full burden. It adds useful behavior beyond the schema: the operation is marked an 'unbilled draft', video inputs yield a video_id for later muxing, and `keep_background_music` splits a music bed for remix. It says nothing about permissions, size/duration limits, latency, or whether uploads are retained, which are notable gaps for an unannotated media-ingest tool.

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?

Front-loaded with the purpose in the first clause, then pipeline guidance, then a compact Args block that exists to fill the zero-coverage schema. Every sentence carries usable information and nothing is padded.

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?

An output schema exists, so return values need not be described, and the pipeline context covers the main follow-on steps. However, for a media-ingest tool with no annotations, the definition never states input constraints (file size, duration, supported codecs beyond extension examples) or how it differs from the 'detailed' sibling.

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 description coverage is 0%, so the description must compensate, and it largely does: it explains that `file_path` is a public HTTPS URL in hosted mode or a local path in stdio mode, enumerates audio and video extensions, gives a language-hint example, and clarifies the effect of `keep_background_music`. Only the format/syntax of `source_language_code` (e.g. ISO codes beyond 'en') is left thin.

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

Purpose4/5

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

The description states a specific verb and resource ('Transcribe speech from an audio or video file') and names the accepted media types. It does not differentiate itself from the sibling 'transcribe_audio_detailed', so an agent cannot tell from the description alone which transcription tool to pick.

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?

It gives explicit downstream usage: feed returned segments to `translate` and then `synthesize_audio` to produce a dubbed track, and notes that video uploads yield a video_id for muxing. It offers no when-not-to-use conditions or comparison against the 'detailed' variant, so a sibling disambiguation gap remains.

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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