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u2n4

video-url-analyzer-mcp

by u2n4

ask_about_video

Ask specific questions about videos or photo posts from TikTok, Instagram, or YouTube. Get answers or track analysis with job ID.

Instructions

Ask a specific question about a video or photo/slideshow post.

Works with videos AND photo/slideshow posts on TikTok, Instagram, and YouTube community posts. YouTube returns the answer immediately. TikTok/Instagram return a job_id — use check_analysis_job(job_id) to poll for the result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe video URL (YouTube, TikTok, Instagram, or other).
modelNoGemini model to use. Defaults to gemini-3.5-flash.gemini-3.5-flash
questionYesYour question about the video.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description only partially covers behavior: it mentions async polling for TikTok/Instagram but does not disclose error handling, rate limits, or authentication requirements.

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?

Three concise sentences, no fluff, and the core action is stated first. Every sentence provides useful information.

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

Completeness4/5

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

The description covers the main workflow and platform differences. An output schema exists, so return values don't need elaboration. Missing authentication hints but adequate for a focused tool.

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?

Input schema has 100% description coverage, so the baseline is 3. The description adds context for the 'url' parameter (platform restrictions) but adds no value for 'model' or 'question' beyond schema.

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 the tool asks questions about videos/photo posts and lists specific platforms, differentiating it from siblings like 'analyze_video' or 'get_transcript'.

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

Usage Guidelines4/5

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

It specifies which platforms are supported and gives platform-specific behavior (immediate vs. job-based results), referencing 'check_analysis_job'. It lacks explicit when-not-to-use guidance but is clear enough for common 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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