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Galbaz1

video-research-mcp

by Galbaz1

Video Comments

video_comments
Read-onlyIdempotent

Fetch top YouTube comments sorted by relevance to analyze audience feedback, returning comment text, like count, and author for each retrieved comment.

Instructions

Fetch top YouTube comments sorted by relevance.

Returns comment text, like count, and author for each comment. Costs 1+ YouTube API units, 0 Gemini units.

Input Schema

NameRequiredDescriptionDefault
urlYesYouTube video URL (youtube.com or youtu.be)
max_commentsNoMaximum comments to fetch (sorted by relevance)

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.0

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive/openWorld, so safety is covered. The description adds genuinely non-structured context: the API quota cost ('1+ YouTube API units, 0 Gemini units') and that results are relevance-sorted. It does not cover pagination or reply handling, keeping it short of a 5.

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?

Three short sentences, purpose front-loaded, then return shape, then cost. Every sentence carries information and nothing is padded.

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 rich annotations and an output schema, the description covers purpose, return fields, and quota cost adequately. Minor gaps remain around pagination behavior and whether comment count interacts with the quota ('1+'), but nothing essential for a correct call is missing.

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 both url and max_comments are fully documented in the schema, and the description's reference to relevance-sorted comments merely echoes the schema. No added format, bounds, or filtering semantics beyond the structured fields, so baseline 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?

States a specific verb and resource (fetch YouTube comments) plus an explicit scope ('top', 'sorted by relevance'). It does not distinguish itself from siblings like video_analyze, video_metadata, or youtube_channel_inspect, so an agent gets a clear purpose but no routing help.

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

Usage Guidelines2/5

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

The description gives no when-to-use guidance, prerequisites, or named alternatives among the ~60 sibling tools. An agent must infer on its own when comment retrieval beats video_analyze or video_metadata.

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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