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Speaker separation

speaker_separation

Start a speaker-separation job for audio already stored in this organization. Returns a job handle immediately; fetch the labeled transcript (txt-ready) later with get_job. Pass audioFileUrl as a storage path from list_files (mimeCategory "audio") or from create_audio_upload_url — this tool does not accept raw or base64 audio. To upload a local file: (1) call create_audio_upload_url, (2) HTTP PUT the raw bytes to signedUploadUrl with the declared Content-Type before the URL expires, (3) call this tool with the returned path as audioFileUrl. After completion, rename speakers with update_speaker_labels.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
audioFileUrlYesStorage path of audio already in this organization (e.g. organizations/<orgId>/files/<name>.mp3). Use list_files (mimeCategory "audio") for a file that is already uploaded, or the path returned by create_audio_upload_url after you HTTP PUT the raw bytes. This tool does not accept raw or base64 audio.
languageCodeNoISO language code that overrides automatic language detection (e.g. "en", "ar"). Omit for auto-detect.
audioMetadataNoOptional filename, mimeType, duration, and size of the uploaded file.
speakersExpectedNoHow many distinct speakers to look for (1–10). Omit to let diarization detect the count.
estimatedDurationSecondsNoDuration estimate in seconds used for create-time credit metering. Omit to charge a 1-minute floor, then reconcile against the processed length.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations declare the mutation profile (readOnlyHint=false, idempotentHint=false), and the description adds genuinely new behavior: the call is asynchronous and returns a job handle immediately rather than results. It also spells out the three-step upload prerequisite, which annotations do not cover. It stops short of any rate-limit or failure-mode detail, so not a full 5.

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?

Front-loaded with the action and return behavior, then the workflow. Dense but each sentence carries operational weight. Minor redundancy between the description's audioFileUrl explanation and the identical schema text keeps it from a 5.

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?

With no output schema, the description correctly fills that gap by naming the return value (job handle) and the retrieval path (get_job). Combined with the upload prerequisite and post-processing step, an agent has everything needed to invoke this tool correctly in sequence.

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 the schema already documents every parameter including the storage-path format, language override, speaker count, and metering behavior. The description largely restates the audioFileUrl constraint rather than adding syntax or format detail beyond the schema, so baseline 3 applies.

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 a specific verb+resource ('Start a speaker-separation job') and immediately scopes it to 'audio already stored in this organization'. An agent can distinguish it from siblings like audio_redaction or meeting_summarizer without opening a schema.

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

Usage Guidelines5/5

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

Explicitly names the alternatives (list_files with mimeCategory "audio", create_audio_upload_url) and states the exclusion ('does not accept raw or base64 audio'). It also gives the follow-up lifecycle path: get_job for results and update_speaker_labels for renaming.

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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