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salviz

Gemini MCP Server

by salviz

gemini_analyze_youtube

Analyze public YouTube videos by summarizing content, transcribing speech, and answering questions using Gemini AI.

Instructions

Analyze a public YouTube video with Gemini (summarize, transcribe, answer questions). Supports up to 10 videos with Gemini 2.5+ models.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesYouTube video URL (e.g., https://www.youtube.com/watch?v=...)
modelNoModel name (default: gemini-3.1-pro-preview)
promptNoPrompt for video analysis (default: Summarize this video)
Behavior3/5

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

No annotations are provided, so the description carries full burden. It mentions that videos must be public and on YouTube, supports batch processing (up to 10 videos), and requires Gemini 2.5+ models. It does not disclose whether the tool downloads the video, what happens with private videos, or any error behavior. This is adequate but not detailed.

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?

Two sentences: the first states the primary action and outputs, the second adds constraints (batch limit, model requirement). No redundant or unnecessary words. Information is front-loaded and efficient.

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 complexity (summarization, transcription, Q&A, batch processing), the description covers the core functionality and key constraints. However, it does not explain output format or structure, how to craft prompts for questions, or error handling. With no output schema, the description should provide more detail on expected returns.

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 100% with each parameter (url, model, prompt) having a description. The tool description adds no additional per-parameter information beyond what the schema already provides. It provides a high-level summary of capabilities, which is expected for baseline scoring.

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 clearly states 'Analyze a public YouTube video' (verb+resource) and lists 'summarize, transcribe, answer questions' as specific capabilities. It distinguishes itself from sibling tools by specifying 'YouTube' and 'public', setting it apart from other gemini_analyze_* tools that handle different media types.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context: YouTube videos, public, with Gemini 2.5+ models, and up to 10 videos. However, it does not explicitly state when to use this tool versus siblings like gemini_analyze_video (for generic video files) or gemini_summarize (for text). No exclusions or alternatives are mentioned.

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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