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emit-ia

YouTube Transcript MCP Server

by emit-ia

youtube_get_channel_transcripts

Extract transcripts from multiple videos in a YouTube channel for analysis, content repurposing, or accessibility purposes.

Instructions

Get transcripts from multiple videos in a YouTube channel

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
channelUrlYesYouTube channel URL
maxVideosNoMaximum number of videos to process
maxConcurrentNoMaximum number of concurrent transcript requests
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal information. It mentions 'multiple videos' and implies batch processing, but doesn't cover critical aspects like rate limits, authentication needs, error handling, or what the output format looks like (transcripts as text, structured data, etc.). This leaves significant gaps for safe and effective tool invocation.

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 directly states the tool's function without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place by conveying essential information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of batch transcript fetching from a channel (3 parameters, no annotations, no output schema), the description is inadequate. It doesn't explain the output format, error conditions, or behavioral constraints like rate limiting. For a tool that likely involves network requests and data processing, more context is needed to use it effectively and safely.

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 schema description coverage is 100%, with clear documentation for all three parameters (channelUrl, maxVideos, maxConcurrent). The description adds no additional parameter semantics beyond what's in the schema, such as explaining how 'maxConcurrent' affects performance or what 'channelUrl' formats are accepted. This meets the baseline for high schema coverage but doesn't enhance understanding.

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 action ('Get transcripts') and resource ('from multiple videos in a YouTube channel'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from siblings like 'youtube_get_playlist_transcripts' or 'youtube_batch_transcripts', which would require more specific scope clarification.

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. With multiple sibling tools for transcripts (e.g., 'youtube_get_playlist_transcripts', 'youtube_batch_transcripts', 'youtube_get_transcript'), there's no indication of whether this is for bulk channel processing versus other use cases, leaving the agent to guess based on tool names alone.

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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