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youtube_get_video_info

Read-only

Fetch YouTube video metadata by ID with brief, standard, or full detail levels, letting AI agents control response size and include chapters, tags, or full descriptions as needed.

Instructions

Get metadata for a YouTube video. Use "detail" to control response size: "brief" (key stats only — title, channel, views, likes, duration), "standard" (default — most fields, truncated description, chapter count), or "full" (everything including full description, chapters, tags, thumbnail).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
detailNoDetail level — "brief" (key metadata only), "standard" (most fields, truncated description, no chapters), or "full" (everything). Default: standard
videoIdYesYouTube video ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly/openWorld/non-destructive, so the safety profile is covered. The description adds genuinely useful operational context beyond that: it enumerates what each detail level returns (stats vs truncated description vs full description, chapters, tags, thumbnail), letting the agent anticipate response payload cost.

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?

Two sentences, purpose front-loaded, followed immediately by actionable detail-level semantics. No filler, no repetition of the tool name, and every clause carries information.

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?

For a two-parameter read tool with annotations and no output schema, the description covers everything needed: what it returns, how to size the response, and the default. Return values are effectively described, so the absence of an output schema is not a gap.

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

Parameters4/5

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

With 100% schema coverage the baseline is 3, but the description adds field-level meaning the schema lacks — e.g. 'brief' explicitly lists title, channel, views, likes, duration. However, it conflicts with the schema on 'standard': the description claims 'chapter count' is included while the schema says 'no chapters', which is a real inconsistency the agent must resolve.

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?

States a specific verb and resource ('Get metadata for a YouTube video') that an agent can immediately distinguish from sibling resources in the list (transcripts, channel videos, downloads, search). The scope is narrow and concrete rather than tautological.

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 guidance exists but only for the `detail` parameter (how to control response size), not for when to pick this tool over siblings such as youtube_get_transcript or youtube_search. No exclusions or prerequisites are stated; the usage is implied by the description rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.