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teobouancheau

YouTube Knowledge MCP

Download YouTube Video

download_video

Download YouTube videos to local storage with quality presets or specific format IDs, providing automatic fallbacks. Returns the file path, title, and format details.

Instructions

Download a YouTube video to local disk. Use the quality parameter for automatic format selection with smart fallbacks, or formatId for a specific format from list_formats. Returns the downloaded file path, title, and format details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
videoYesYouTube video ID (e.g., dQw4w9WgXcQ) or full URL
qualityNoQuality preset with smart fallback. "best" selects highest available. Specific resolutions fall back to next best if unavailable. "audio" extracts audio only. Default: best
formatIdNoSpecific format code from list_formats (e.g., "22", "137+140" for combined). Overrides quality when provided.
outputDirNoOutput directory path. Default: ~/.youtube-knowledge/downloads/
Behavior3/5

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

Annotations already indicate readOnly=false, so the write nature is known. The description adds that the write is to 'local disk' and discloses the return value (file path, title, format details), which annotations do not cover. However, it does not mention other behavioral traits such as overwriting behavior or error handling, so it offers minimal but non-redundant value.

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 sentences long and front-loads the core purpose, followed by parameter guidance and return value. No words are wasted, and it is well-structured for quick parsing by an agent.

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 no output schema, the description appropriately summarizes the return values. It covers the key parameter choices and gives enough context to use the tool effectively. It does not address edge cases like failures or file conflicts, but the annotations and schema fill in most missing details for a download tool.

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 coverage is 100%, with each parameter fully described. The description adds a small cross-reference between quality and formatId, but largely repeats what the schema already states. Since the schema does the heavy lifting, a baseline score of 3 is appropriate with only marginal added meaning.

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 clearly states the action ('Download') and the resource ('a YouTube video to local disk'), distinguishing it from sibling tools like get_video_info or list_formats. It also specifies the function's output (file path, title, format details), leaving no ambiguity.

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 gives explicit internal guidance on when to use quality vs formatId, and references list_formats to obtain format codes. It does not explicitly state when to use this tool versus alternatives (e.g., when only metadata is needed), but the clear purpose and parameter guidance provide adequate context.

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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