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yunlinwu

youtube-transcript-mcp

by yunlinwu

search_transcript

Search a YouTube video transcript for keywords and retrieve matching segments with timestamps and contextual text.

Instructions

Search a YouTube video's transcript for matching segments.

Args: url: YouTube video URL or video ID query: Search term to find in the transcript lang: Language code for captions (default: "en") context_seconds: Seconds of context around each match (default: 30)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
langNoen
queryYes
context_secondsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description carries full burden for behavioral disclosure. It mentions context_seconds but omits details about output format, timestamps, rate limits, or authentication needs. The minimal description leaves significant behavioral gaps.

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 very concise: one sentence summary followed by a bulleted list of arguments. Every sentence adds value with no redundancy. Structure is clear and scannable.

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 has 4 parameters, no annotations, and an output schema exists, the description covers basic requirements. However, it does not address error conditions, prerequisites (e.g., video must have captions), or the structure of returned segments, leaving some gaps.

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 coverage is 0%, so the description must compensate. It provides brief explanations for all four parameters (url, query, lang, context_seconds) that add meaning beyond property names, but the explanations are minimal and lack format constraints or examples.

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 searches a YouTube video's transcript for matching segments, using specific verb and resource. It distinguishes from the sibling get_transcript_tool by implication (search vs. full retrieval), but does not explicitly contrast them.

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?

No guidance is provided on when to use this tool versus the sibling get_transcript_tool or any alternatives. The description simply states what it does without usage 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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