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YoutubeComments

youtube_comments
Read-only

Fetch and explore YouTube video comments: view top-level reactions or drill into specific reply threads to understand what viewers are saying about a video.

Instructions

Read YouTube video comments: top-level overview or per-thread drill-down.

Pivot from youtube when the goal is to read what viewers are saying about a video. The video tool returns the description; this tool returns the conversation.

Two views, selected by whether comment_id is set:

  • Overview (no comment_id): top-level comments sorted by 'top', each with author, score, pinned/uploader badges, and a yt-dlp comment id for drill-down. No replies.

  • Thread (comment_id=): the target top-level comment plus its replies (up to 50 per thread).

The flow matches how a human reads YouTube comments: skim top-level statements for what people thought of the video, then drill into threads that look interesting (high score, pinned, uploader replied).

URL formats accepted: same as the youtube video action — watch?v=, youtu.be/, shorts/, clip/, embed/, v/.

No authentication required. Comment-fetch failures (bot detection, private video, age-restricted) surface as user-facing error strings via the same exception mapping as youtube.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesYouTube video URL. Same forms as the Youtube tool's video action: watch?v=, youtu.be/, shorts/, clip/, embed/, v/.
limitNoTop-level overview cap. Default 30, capped at 50. yt-dlp returns comments by 'top' sort (highest score first); the cap constrains how many are rendered. Ignored when comment_id is set.
comment_idNoDrill into a specific top-level comment's thread. The id comes from the overview view's id= field on each entry. Omit for the top-level overview.
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses key behaviors: top-level comments are sorted by 'top' with no replies, thread view shows up to 50 replies, no authentication required, and errors like bot detection are surfaced as user-facing strings. This adds substantial behavioral context.

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 well-structured with a front-loaded summary, clear sections for the two views, usage flow, URL formats, and error handling. Every sentence adds value, and the format aids quick comprehension despite its length.

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

Completeness5/5

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

Given the tool's complexity (two views, no output schema, interactions with YouTube), the description is complete: it covers how to use it, what to expect in returns, limitations (cap, no replies in overview), and failure modes. It leaves little ambiguity for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Even though schema coverage is 100%, the description adds meaning beyond the schema: comment_id selects the thread view, limit caps the overview and is ignored with comment_id set, and the comment id source is described as coming from the overview's id field. This enriches the parameter semantics.

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 opens with a specific verb and resource: 'Read YouTube video comments: top-level overview or per-thread drill-down.' It explicitly distinguishes itself from the sibling 'youtube' tool by stating 'The video tool returns the description; this tool returns the conversation,' making its purpose unambiguous.

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

Usage Guidelines5/5

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

It provides explicit when-to-use guidance: 'Pivot from youtube when the goal is to read what viewers are saying about a video.' It also explains the two usage modes (overview vs. thread) based on comment_id, giving clear context for selecting this tool over alternatives.

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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