Skip to main content
Glama

get_video_translation_status

Check a video translation task's status by order number, returning its current state (pending, running, completed, failed, or cancelled) and progress step.

Instructions

查询单个视频翻译任务的状态。上游是 SSE 流,本工具取第一帧数据就返回,不会挂住。状态:0 未开始 / 1 进行中 / 2 成功 / 3 失败 / 4 已取消——注意 2 就是完成,和文档翻译的状态码不是一套,别混用。进行中时 step 表示阶段(1 语音识别 / 2 字幕翻译 / 3 语音生成)。任务通常要几分钟,建议 10-30 秒查一次,并把进度转述给用户。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
localeNo把要念给用户听的那部分文案(任务状态、产出说明、进度行、失败原因、下载说明)输出成哪种语言。按用户当前说话的语言填,不确定就别传——不传取服务端 MCP_LOCALE,再没有就是 zh。
order_noYes视频翻译任务订单号

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior5/5

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

The description transparently discloses behavior beyond the minimal annotation: it returns immediately after the first SSE frame (does not hang), defines all status codes (0-4) with a warning not to confuse with document translation codes, explains step meanings, and recommends a polling interval. This is substantial transparency.

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 reasonably concise but includes essential contextual warnings and usage advice. It is front-loaded with the core purpose and flows logically through behavior, status codes, steps, and polling recommendation, making it well-structured.

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 covers the tool's purpose, non-blocking behavior, status code meanings, step meanings, polling advice, and locale guidance. It lacks an explicit mention of the response format, but the status and step explanations provide sufficient context for a status query tool.

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?

The input schema already provides comprehensive descriptions for both parameters, especially locale (purpose, fallback to MCP_LOCALE, default zh). The tool description adds no additional parameter clarification, so the baseline for high schema coverage 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?

The description explicitly states the tool queries the status of a single video translation task ('查询单个视频翻译任务的状态'), clearly specifying the action and resource. This distinguishes it from sibling tools like get_video_rewrite_status or get_document_translation_status.

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 advises polling every 10-30 seconds and warns about the status code difference from document translation, giving practical guidance. It does not explicitly mention alternatives like wait_for_video_translation, but the non-hanging behavior ('不会挂住') implicitly suggests this tool is suitable for polling.

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

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/zhang452064326/belindoc-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server