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youtube_comment

Destructive

当用户需要 YouTube 评论信息、YouTube 视频评论、YouTube 评论列表、YouTube comment、视频评论信息,与采集、抓取、爬取、获取、提取等动词组合时触发。提交 YouTube 评论信息采集 Builder 任务,采集器标识固定为 youtube_comment_by-id。

Input Schema

NameRequiredDescriptionDefault
sort_byNo评论排序方式,该参数用于指定 YouTube 评论排序。用于 youtube_comment_by-id,可选值:Top comments、Newest first,默认值为 Top comments。Top comments
video_idYes视频唯一 ID,该参数用于指定待采集的 YouTube 视频的唯一 ID。用于 youtube_comment_by-id。调用方必须提供非空值,不使用默认值。
file_nameNoBuilder file_name 字段。不传默认为 {{TasksID}}。{{TasksID}}
load_repliesNo加载回复,该参数用于指定页面加载回复时用到的时间。用于 youtube_comment_by-id,默认值为 10。10
num_of_commentsNo评论数量,该参数用于指定需要采集的评论数量。用于 youtube_comment_by-id,默认值为 10。10

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare destructiveHint=true, readOnlyHint=false, idempotentHint=false and openWorldHint=true, covering the safety profile. The description adds that this is an async Builder task submission with a fixed collector ID, which is useful context, but it never explains that the call returns a task handle requiring later polling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The informative sentence about submitting the Builder task is well placed, but the leading trigger sentence is a repetitive keyword list ('YouTube 评论信息、YouTube 视频评论、YouTube 评论列表...') that adds little beyond noise. It is not egregiously long but wastes space on redundant synonyms.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 5-parameter task-submission tool with no output schema, the description conveys the core action but omits the async workflow (task ID return, polling via scraper_task_status/result) that an agent needs to actually use the result. Annotations carry the safety profile, so the remaining gap is the task lifecycle.

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%, so all five parameters (video_id, sort_by, load_replies, num_of_comments, file_name) are already fully documented in the schema. The description adds no additional parameter meaning, so the baseline of 3 applies.

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 second sentence states a specific verb+resource: it submits a YouTube comment collection 'Builder' task with a fixed collector ID (youtube_comment_by-id). This distinguishes it from siblings like youtube_video or youtube_transcript. The first sentence is largely keyword stuffing, but the core purpose is identifiable.

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?

The first sentence lists trigger conditions (when a user needs YouTube comment info combined with collect/scrape/fetch verbs), which is implied usage context. However, it names no alternatives and gives no exclusions or prerequisites, so it is closer to keyword matching than genuine decision guidance.

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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