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get_job_status

Check a dubbing job's status and retrieve the dubbed video and subtitle download URLs when completed. Get error details and refund if failed.

Instructions

Check a dubbing job's status.

Once the status is "completed" the response also carries the dubbed video and subtitle download URLs. "failed" carries the error and means the credits were refunded.

Args: job_id: The job_id returned by submit_dubbing_job.

Returns: JSON with status ("processing" / "completed" / "failed" / "cancelled") and, for a completed job, final_video_url and subtitle_url.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.5/5.0
Behavior5/5

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

No annotations are provided, so the description fully carries the burden. It discloses the four possible statuses, the presence of download URLs on completion, the error field on failure, and the side effect of credit refund on failure. This goes well beyond the schema and covers key behavioral outcomes.

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?

The description is well-structured with a brief opening, followed by Args and Returns sections. It is slightly longer than strictly necessary, but every sentence adds useful detail (statuses, URLs, error handling). No redundancy or filler.

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?

For a single-parameter status-check tool with an output schema, the description covers all essential information: possible statuses, what the response contains for each state, and the refund side effect. It is complete enough for an agent to call correctly and interpret results.

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?

The schema only states job_id is an integer and required. The description adds the critical semantic context that job_id is the value returned by submit_dubbing_job, which fully explains how to obtain a valid input. With 0% schema description coverage, this is essential and well handled.

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 opens with a clear verb and resource: 'Check a dubbing job's status.' It explicitly ties job_id to submit_dubbing_job, which distinguishes it from the cost-estimation and submission tools. The resource and action are unambiguous.

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?

It clearly implies the tool is for checking status after submission, and references where job_id comes from. However, it does not explicitly contrast with the wait_for_job sibling or state when to prefer one over the other. The guidance is present but not explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.