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tejas-borate-wai

YouTube Insights MCP Server

get_youtube_metadata

Extract video metadata including title, author, and thumbnail from YouTube videos using the URL or video ID for analysis and data processing.

Instructions

Get metadata for a YouTube video including title, author, and thumbnail.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesYouTube video URL or video ID
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves metadata but does not cover critical aspects such as rate limits, authentication needs, error handling, or response format. This leaves significant gaps for a tool that interacts with an external service like YouTube.

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 a single, efficient sentence that front-loads the core purpose and includes specific examples of metadata fields. There is no wasted verbiage, making it highly concise and well-structured for quick understanding.

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?

Given the tool's low complexity (one parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral traits and usage context, which are important for external API interactions. Without an output schema, it also does not explain return values, though this is not required.

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?

The input schema has 100% description coverage, clearly documenting the 'url' parameter as accepting a 'YouTube video URL or video ID'. The description does not add any semantic details beyond this, so it meets the baseline score of 3 where the schema does the heavy lifting.

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 description clearly states the tool's purpose with a specific verb ('Get') and resource ('metadata for a YouTube video'), and lists key metadata fields (title, author, thumbnail). However, it does not explicitly differentiate from sibling tools like 'get_youtube_insights' or 'get_youtube_transcript', which likely retrieve different types of video information.

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 provides no guidance on when to use this tool versus its siblings (e.g., 'get_youtube_insights' for analytics or 'get_youtube_transcript' for text content). It implies usage for basic video metadata but lacks explicit context, alternatives, or exclusions, leaving the agent to infer based on tool names alone.

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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