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speechweave

@speechweave/mcp

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by speechweave

Start job from local file (async)

start_job_file

Upload a local audio or video file for transcription, receiving an immediate job ID for later polling. Ideal for long recordings.

Instructions

Upload a local audio/video file and return a job id immediately without waiting. Use for long recordings or when you will poll later with get_job_status. Pass an absolute filesystem path.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesAbsolute local filesystem path to an audio or video file. Relative paths are rejected. Do not pass raw binary over MCP.
modelNoTranscription model tier. core = default balance of speed/accuracy; max = hardest audio.core
languageNoOptional two-letter ISO language code (e.g. en, es).
service_modeNodeferred = background queue (default, better for long audio); synchronous = higher-priority path with a smaller size cap.deferred
Behavior3/5

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

No annotations provided, so description must carry behavioral disclosure. It reveals async nature and job ID return but lacks detail on failure modes, file read mechanism, or size limits.

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?

The description is two sentences with no wasted words. It front-loads the purpose and follows with usage guidance, achieving maximum conciseness.

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 good schema coverage and sibling context, the description adequately covers purpose and usage. Missing output schema is partially compensated by mentioning job ID and polling pattern. Could hint at return structure.

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 coverage is 100%, so baseline is 3. Description adds minimal value by emphasizing the absolute path requirement, but does not explain model, language, or service_mode beyond what schema already provides.

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?

The description clearly states the tool uploads a local audio/video file, returns a job id immediately, and is async. It distinguishes from siblings like start_job_url (URL input) and transcribe_file (sync).

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?

The description explicitly advises using this for long recordings or when polling with get_job_status, implying alternatives for other cases. However, it does not name all sibling tools (e.g., transcribe_file) directly.

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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