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SocialDataX YouTube MCP

youtube_submit_video_speech_text_by_url

提交 YouTube 视频口播转文字任务;提交后最多等待 240 秒,未完成时返回 job_id 和下一步查询动作。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
video_urlYesYouTube 视频页面链接;支持 watch、youtu.be 短链和 Shorts 链接。从搜索结果提交口播转文字任务时,直接传搜索结果里的 share_url(items[*].share_url);不要传频道链接、播放列表链接、搜索页链接或裸 video_id。

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorYes失败或过期时的稳定错误结构;非终态或成功时为 null。
job_idYes任务 ID。
statusYes任务状态。
messageYes面向用户/AI 的状态说明。
platformYes任务所属平台。
source_idYes任务来源 ID。
content_idYes平台内容 ID。
transcriptYes成功时的口播转文字结果;非终态或失败时为 null。
is_terminalYes是否已终态。
next_actionYes非终态时建议的下一步查询动作。
content_metaYes作品上下文信息,便于结合转写内容做口播分析。
content_typeYes内容类型。
next_poll_after_secondsYes建议下次查询前等待的秒数;非终态时可用。

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

The description discloses meaningful behavioral traits beyond annotations: the operation may wait up to 240 seconds, and if not completed it returns a job_id plus a next query action. This gives the agent a clear model of the asynchronous task lifecycle. No contradiction with annotations exists.

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 a single focused sentence that front-loads the action and resource, then states the timeout and fallback behavior. Every clause provides necessary operational information with no wasted words.

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 is largely complete for an async submission tool: it specifies wait time, job_id return, and next-step instruction. The output schema covers return details, and the URL parameter constraints are in the schema. A minor gap is that the 'next query action' is not concretely named, and the sibling by_video_id alternative is not referenced, though both are inferable from context.

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 covers the only parameter, video_url, with 100% coverage and a rich description of accepted URL formats and exclusions. The main tool description adds no additional parameter semantics, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific action (submit a YouTube video speech-to-text task) and the resource (YouTube video by URL). It is obvious what the tool does, but it does not explicitly differentiate this from the sibling youtube_submit_video_speech_text_by_video_id within the description text itself.

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

Usage Guidelines2/5

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

There is no guidance about when to use this tool versus the by_video_id variant or when not to use it. The tool name implies the distinction, but the description itself provides no usage context or alternative selection hints.

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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