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get_youtube_transcript

Extract clean transcript text from any YouTube video URL to read, summarize, search, or save content without watching.

Instructions

Extract the subtitle/transcript text from a YouTube video URL. Always use this tool when:

  • User provides a YouTube URL and wants to read/analyze the video content

  • User asks what a YouTube video is about or wants a summary

  • User needs to extract quotes or information from a YouTube video

  • User wants to search through video content without watching

  • User needs the transcript saved to a file for reference

Returns the clean text content of the video's English subtitles (auto-generated or manual).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe YouTube video URL (e.g., https://www.youtube.com/watch?v=VIDEO_ID)
save_to_fileNoWhether to save the transcript to a file (default: true). Files are saved to the directory specified by YT_SUBS_DOWNLOAD_DIR environment variable, or ~/Downloads/yts/ if not set.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.6

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. It does state the return value ('clean text content of the video's English subtitles') and mentions saving to a file in the use cases. However, it does not disclose the default file-saving side effect (save_to_file defaults to true) or failure behavior when no subtitles are available.

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 core purpose is front-loaded, and the bulleted triggers are scannable and actionable. Some bullets overlap semantically, but the structure remains efficient and each bullet contributes to routing an agent to the correct tool.

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?

For a simple two-parameter tool, the description covers what it does, when to use it, and what it returns. Minor gaps like default file-writing behavior and no-subtitle error handling are either represented in the schema or are edge cases that do not prevent correct invocation.

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%, so both parameters are already fully documented in the input schema. The description adds only general context about the URL and file-saving use case, not new syntax or format details, so the baseline 3 applies.

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 opens with a specific verb and resource: 'Extract the subtitle/transcript text from a YouTube video URL.' The bulleted use cases further clarify exactly what the tool is for, making its purpose unambiguous even without sibling tools.

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 provides explicit 'Always use this tool when' triggers covering summarization, quoting, searching, and saving transcripts. It lacks explicit when-not-to-use guidance or named alternatives, but no sibling tools exist, so the positive triggers give clear routing 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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