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transcribe

Transcribe speech in an audio file to text using CleanAudio speech-to-text.

Input Schema

NameRequiredDescriptionDefault
filenameNoOptional filename hint including extension, e.g. episode.mp3
languageNoLanguage name for transcription, default "English"English
audio_urlNoHTTP(S) URL of the audio file to process
audio_base64NoBase64-encoded audio (raw or data URI)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations at all, the description carries the full disclosure burden but says nothing about authentication, size/duration limits on audio, supported formats, latency, cost, or what the response contains. A mutation-free read operation is safe to assume, but an agent gets nothing about constraints or failure modes, and there is no output schema to compensate.

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

Conciseness4/5

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

A single front-loaded sentence naming the action, input, output, and engine with no filler. It is efficient, though it errs toward under-specification rather than over-verbosity.

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

Completeness2/5

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

No annotations, no output schema, and four optional parameters create a real gap: an agent doesn't know what the return value looks like, whether languages are restricted, whether one of the audio inputs is mandatory, or how large a file can be. The one-line description doesn't fill any of these gaps.

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?

Schema description coverage is 100%, so filename, language, audio_url, and audio_base64 are already documented. The description adds no parameter meaning beyond that baseline, and notably omits the likely mutual exclusivity of audio_url vs. audio_base64 that the schema also doesn't enforce (required list is empty).

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?

Names a specific verb and resource: transcribe speech in an audio file to text, plus the underlying engine (CleanAudio speech-to-text). It doesn't distinguish itself from sibling tools, notably text_to_speech (the inverse direction), leaving the agent to infer the direction from the name alone.

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

Usage Guidelines3/5

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

Usage is only implied by the verb 'transcribe' – there is no explicit when-to-use statement, no mention of when to prefer a sibling like text_to_speech or clean_noise preprocessing, and no guidance on choosing between audio_url and audio_base64 inputs.

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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