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tulaman

youtube-watchlater-mcp

by tulaman

get_subtitles

Downloads auto-generated subtitles for any YouTube video using yt-dlp and returns the VTT track content.

Instructions

Downloads auto-generated subtitles for a YouTube video via yt-dlp and returns the VTT content.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoSubtitle language code, e.g. "en" or "ru".en
videoYesYouTube video URL or bare video ID (e.g. dQw4w9WgXcQ).
browserNoWhich browser to read YouTube cookies from.chrome
profileNoBrowser profile name, e.g. "Default" or "Profile 1".
Behavior3/5

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

With no annotations, the description carries full burden. It discloses that subtitles are auto-generated, that yt-dlp is used, and that the output is VTT content, which is useful context. However, it does not mention potential failures (e.g., subtitles unavailable, network errors), rate limits, or the need for YouTube cookies, which are notable behavioral aspects of this tool.

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, well-structured sentence that front-loads the action and includes essential information (tool, method, output). No word is wasted, and it is easy to parse.

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?

The description provides a reasonable overview for a straightforward tool, but with no output schema, it could clarify what happens when subtitles are not found or how the VTT content is returned (e.g., as a file path, string). The complexity is moderate due to 4 parameters, but the description does not fully cover edge cases or the exact behavior of the browser/profile parameters.

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%, and each parameter has a clear description (e.g., 'Subtitle language code', 'YouTube video URL or bare video ID'). The tool description adds little beyond this, but since the schema is complete, the baseline of 3 is appropriate. It does not explain how parameters interact (e.g., browser/profile for cookie access) beyond what schema already states.

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 uses a specific verb ('Downloads') and clearly identifies the resource ('auto-generated subtitles for a YouTube video'), method ('via yt-dlp'), and output ('VTT content'). This distinguishes it from the sibling tool get_watch_later, which has a different purpose.

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?

The description implies usage when subtitles for a YouTube video are needed, and the inclusion of browser/profile parameters hints at cookie-based authentication, but it does not explicitly state when to use this tool instead of alternatives or provide exclusionary conditions. The alternative (get_watch_later) is unrelated, so no direct comparison is given.

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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