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emit-ia

YouTube Transcript MCP Server

by emit-ia

youtube_search_transcript

Search for specific text within YouTube video transcripts to locate relevant content quickly. Enter a video URL and search query to find matching segments with configurable context options.

Instructions

Search for specific text within a YouTube video transcript

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesYouTube video URL
queryYesText to search for in the transcript
contextWindowNoSeconds of context to include before/after matches
caseSensitiveNoWhether search should be case sensitive
languageNoLanguage code for transcripten
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. It states the search function but doesn't cover aspects like rate limits, authentication needs, error handling, or what the output format might be (e.g., list of matches with timestamps). This leaves significant gaps for a tool that likely interacts with external APIs.

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 ('search for specific text') and resource ('within a YouTube video transcript'), making it easy to parse quickly.

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 searching transcripts (likely involving API calls) and the lack of annotations and output schema, the description is insufficient. It doesn't explain what the search returns (e.g., matches with context), potential limitations (e.g., transcript availability), or integration details, leaving the agent under-informed for effective use.

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 description adds no parameter-specific information beyond what's already in the schema, which has 100% coverage with clear descriptions for all 5 parameters. Since the schema fully documents the inputs, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract from the schema's completeness.

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 verb ('search') and resource ('within a YouTube video transcript') with specificity about the search target ('specific text'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'youtube_get_transcript' or 'youtube_transcript_summary', which might also involve transcript retrieval or processing.

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, such as 'youtube_get_transcript' for full transcripts or 'youtube_transcript_summary' for summaries. It mentions the action but lacks context about prerequisites, limitations, or comparisons to sibling tools, leaving the agent to infer usage scenarios.

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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