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check_transcription_status

Check whether a transcription job is complete, still running, or failed by providing its job ID. Poll every 10–15 seconds to know when results are ready.

Instructions

[EXPERIMENTAL] Check the status of a running transcription job. Call this after starting transcribe_audio, transcribe_to_labels, or transcribe_to_file. Poll every 10-15 seconds until status is 'complete' or 'error'.

Args: job_id: The job ID returned when you started the transcription.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYes
Install Server

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of explaining behavior. It mentions the polling behavior and the expected terminal statuses, which is informative. However, it does not explicitly state that the tool is non-destructive (read-only) or describe potential error conditions, leaving some room for interpretation.

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 concise, consisting of two sentences. It front-loads the purpose and then provides the usage context. There is no redundant information, and every phrase contributes to clarity.

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?

The description gives sufficient context for a simple tool: it indicates when to call it (after initiating transcription) and what the outcome will look like (status 'complete' or 'error'). It does not explicitly describe the return format, but the mention of status values implies the response contains the status. Given the tool's simplicity and no output schema, this is adequate.

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?

Although the schema has no description for the job_id parameter, the description text clearly explains: 'The job ID returned when you started the transcription.' This fully compensates for the lack of schema-level documentation, providing the agent with the exact source and meaning of the parameter.

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's purpose: checking the status of a running transcription job. It uses a specific verb ('check') and resource ('transcription status'), which distinguishes it from other transcription-related tools like transcribe_audio or transcribe_to_labels.

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?

The description explicitly instructs when to call this tool ('after starting transcribe_audio, transcribe_to_labels, or transcribe_to_file') and how to use it (poll every 10-15 seconds until status is 'complete' or 'error'). This provides clear usage guidance and differentiates it from other status-check tools like check_pipeline_status.

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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