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xnomi05-blip

YouTube MCP Server

by xnomi05-blip

get_video_comments

Fetch top-level comments from a YouTube video to gauge audience response. Returns author, text, like count, reply count, and publish date.

Instructions

Fetch top-level comments from a YouTube video. Returns author, text, like count, reply count, and publish date.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesYouTube video URL or video ID
orderNoSort order (default: relevance)
max_resultsNoNumber of comments (1-100, default: 20)
Behavior3/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It usefully states that only top-level comments are returned and lists the output fields. However, it omits pagination behavior, potential rate limits, and how missing or disabled comments are handled, which are relevant for an agent planning repeated calls.

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 two concise sentences with no filler. The primary action and resource are front-loaded, and the second sentence efficiently summarizes the return payload.

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 simple read-only tool, the description is largely complete: it names the resource, the result fields, and the top-level scope. It would benefit from a mention of pagination or reply behavior, but the schema covers parameter constraints and the tool is straightforward enough that the missing items are minor gaps.

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?

Since the input schema already has 100% description coverage for all three parameters, the baseline is 3. The tool description adds general context about returning top-level comments and fields, but it does not add new meaning to specific parameters such as 'order' or 'max_results' beyond what the schema already states.

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 'Fetch' and a clear resource: top-level comments from a YouTube video. It also enumerates the returned fields, making the tool's function immediately obvious and distinct from sibling tools that handle metadata, transcripts, or trending searches.

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 provides clear context: use this tool when you need top-level comments on a video. It does not explicitly exclude alternatives or give when-not-to-use guidance, but the scope is specific enough that an agent can infer appropriate usage without confusion.

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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