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SocialDataX YouTube MCP

youtube_submit_video_speech_text_by_video_id

根据 YouTube video_id 提交口播转文字任务;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_idYesYouTube 视频 ID,必须是 11 位字符串;可直接使用搜索结果 items[*].video_id。不要传视频链接、频道链接、播放列表链接或搜索页链接。

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

A4.2/5.0
Behavior4/5

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

The description adds useful behavioral context beyond annotations: it reveals the tool is an async submission that waits up to 240 seconds and returns a job_id with a next query action when incomplete. Annotations already indicate a non-read-only, non-idempotent operation, so this behavior disclosure is valuable and not contradictory.

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 compact sentence that front-loads the main action, then adds the critical timeout and fallback behavior. There is no filler or redundant information.

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?

For a one-parameter async submission tool with an output schema, the description sufficiently covers the task, the wait limit, and the job_id handoff for incomplete results. It could be slightly more explicit about the completed-case response and the exact sibling for querying the job, but those are inferable from the schema and sibling names.

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 description coverage is 100%, and the schema itself provides detailed semantics for video_id: 11-character ID, use from search results, and do not pass links. The tool description only restates 'video_id' without adding semantic detail, so the baseline of 3 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 states a specific verb ('提交'), a specific resource ('口播转文字任务' / speech-to-text task), and a specific input basis ('根据 YouTube video_id'). It also distinguishes itself from the by-URL sibling by emphasizing video_id, and clarifies the async submission behavior.

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 gives clear context for when to use the tool: when you have a YouTube video_id and need to submit a speech-to-text job. It also explains the post-submission flow (wait up to 240 seconds, then receive job_id if not complete). It does not explicitly name alternatives or exclusions, but the by-URL sibling is easily inferable from the naming.

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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