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Glama

get_video_info

Fetch YouTube video metadata—title, channel, duration, upload date, and live status—from a video URL so users can identify and verify content before transcription.

Instructions

Fetch YouTube video metadata (title, channel, duration, upload date, live status).

Args: url: YouTube video URL.

Input Schema

NameRequiredDescriptionDefault
urlYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the burden; 'Fetch ... metadata' does imply a non-destructive read, and the output schema covers the return shape. It says nothing about invalid/non-video URLs, private or age-restricted videos, live-stream edge cases, or any rate limiting or auth, which are the real failure modes for a YouTube fetch.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The payload is one front-loaded sentence enumerating exactly what is returned, with zero filler. The trailing 'Args: url: YouTube video URL' block is slightly redundant with the schema but does add the video-vs-channel qualifier.

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?

For a one-parameter read tool with an output schema, this is close to sufficient — the return fields are named and the parameter is scoped. What is missing is disambiguation from the four siblings and any hint about error behavior, which an agent needs before deciding to call it.

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 0%, so the description must compensate. It does document the single parameter and usefully narrows it to a 'YouTube video URL' (ruling out channel or playlist URLs), but it gives no accepted formats (watch?v=, youtu.be, shorts) or validation behavior.

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 gives a specific verb ('Fetch') and resource ('YouTube video metadata') and even enumerates the returned fields (title, channel, duration, upload date, live status). It implicitly separates itself from siblings like transcribe_youtube and list_channel_videos by returning metadata for a single video, though it never names an alternative explicitly.

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?

There is no when-to-use guidance: nothing states that this is for a single video rather than a channel, or that transcript text requires transcribe_youtube instead. The agent must infer the selection rule from the tool name alone.

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