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유튜브 댓글 조회

youtube_comments
Read-only

List comments of a public YouTube video sorted by top or newest, with author, text, likes, pinned/hearted flags and optional replies. 유튜브 공개 영상의 댓글을 인기순 또는 최신순으로 조회합니다. [호출당 30포인트]

Input Schema

NameRequiredDescriptionDefault
urlYes유튜브 영상 URL 또는 11자리 영상 ID
sortNotop(인기순, 기본)·new(최신순)
countNo받을 댓글 수 1~200 (기본 20, 답글 포함)
repliesNotrue면 댓글마다 답글을 최대 5개까지 함께 받습니다 (기본 false)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / count / description
      Previous value: -"가져올 댓글 수 1~200 (기본 20, 답글 포함)"New value: +"받을 댓글 수 1~200 (기본 20, 답글 포함)"
    • changedInput schema / properties / replies / description
      Previous value: -"true면 댓글마다 답글을 최대 5개까지 함께 가져옵니다 (기본 false)"New value: +"true면 댓글마다 답글을 최대 5개까지 함께 받습니다 (기본 false)"
  2. Added

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds genuinely useful context beyond them: the operation only works on public videos, and it costs 30 points per call, which is a real invocation-side constraint. It does not describe pagination or what happens when a video has no comments.

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?

Front-loaded with the English statement of scope and return fields, followed by the Korean equivalent and a bracketed cost tag. Efficient overall, though the bilingual duplication means the same content is effectively delivered twice.

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?

With no output schema, the description usefully summarises the return shape (author, text, likes, pinned/hearted flags, replies), and with 100% schema coverage the parameter side is handled. Only pagination/edge-case behaviour is left unspecified, which is minor for a list tool with a bounded count parameter.

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 four parameters (url, sort, count, replies) are already documented in the schema, including defaults and limits. The description only restates the sort modes and the notion of optional replies, adding no format or edge-case detail beyond the schema. Baseline 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?

States a specific verb and resource ('List comments of a public YouTube video') and even enumerates the returned fields (author, text, likes, pinned/hearted flags, replies). It is clearly distinguishable from other YouTube siblings like youtube_subtitle or youtube_metadata, though it doesn't explicitly name an alternative it is not.

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?

Usage is implied rather than stated: use it when you need comments, with 'top' or 'new' ordering. There is no when-not guidance (e.g. private/age-restricted videos, or how it relates to crawl_youtube), and no prerequisites beyond the implicit 'public' qualifier. The per-call point cost is the only usage-relevant caveat given.

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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