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emit-ia

YouTube Transcript MCP Server

by emit-ia

youtube_transcript_summary

Generate formatted summaries from YouTube video transcripts to extract key information quickly. Choose brief, detailed, topic-based, or timestamped summaries.

Instructions

Get a formatted summary of transcript content

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesYouTube video URL
summaryTypeNoType of summary to generatebrief
languageNoLanguage code for transcripten
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'gets' a summary, implying a read-only operation, but doesn't clarify if it requires authentication, has rate limits, or how it handles errors (e.g., missing transcripts). For a tool with no annotation coverage, this is a significant gap in describing operational behavior.

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, efficient sentence that front-loads the core purpose ('Get a formatted summary of transcript content') with zero wasted words. It's appropriately sized for a tool with a straightforward function, making it easy for an agent to parse quickly.

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?

Given the tool's moderate complexity (3 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral traits, usage context, and output format. Without an output schema, the description should ideally hint at the return value (e.g., 'summary text'), but it doesn't, leaving gaps in completeness.

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?

The input schema has 100% description coverage, with clear documentation for all parameters (url, summaryType, language), including enums and defaults. The description adds no additional parameter semantics beyond what's in the schema, such as format details or constraints. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't need to.

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 clearly states the tool's purpose as 'Get a formatted summary of transcript content', which specifies the verb ('get'), resource ('transcript content'), and output format ('formatted summary'). However, it doesn't explicitly differentiate from sibling tools like 'youtube_get_transcript' or 'youtube_search_transcript', which might handle raw transcripts or search within them rather than generating summaries.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'youtube_get_transcript' for raw transcripts or 'youtube_search_transcript' for searching within transcripts, nor does it specify prerequisites or exclusions (e.g., video must have captions). This leaves the agent with minimal context for tool selection.

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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