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aigentive
by aigentive

analyze_youtube_video

Analyze YouTube video content by submitting a URL and a custom prompt. Supports multi-turn sessions for contextual follow-up queries.

Instructions

Single-shot or session-integrated YouTube video analysis using direct URL method.

Args: youtube_url: YouTube video URL or ID prompt: Analysis instruction model: Gemini model to use session_id: Optional session for context

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
youtube_urlYes
promptYes
modelNogemini-2.5-flash
session_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description must bear the burden of behavioral disclosure. It only lists parameters and does not describe important traits such as whether the video is downloaded, processing time, supported video lengths, or any rate limits. The presence of an output schema is not utilized for transparency.

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 with a brief introductory sentence and a structured parameter list. No wasted words; each sentence serves a purpose. The key purpose is front-loaded.

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 and an output schema, the description covers parameter semantics but lacks behavioral context and return value explanation. It provides a minimum viable description but does not fully equip an agent to understand side effects or expected outcomes beyond the schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, meaning the input schema has no descriptions. The tool description provides brief but meaningful parameter descriptions (e.g., 'YouTube video URL or ID', 'Analysis instruction', 'Gemini model to use', 'Optional session for context'), which add value beyond the bare property names.

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's purpose: 'Single-shot or session-integrated YouTube video analysis using direct URL method.' It explicitly mentions YouTube video analysis by URL, distinguishing it from siblings like analyze_local_video and analyze_video_in_session.

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 use for YouTube URLs and mentions optional session integration via session_id. However, it does not explicitly state when to use this tool over siblings (e.g., analyze_local_video for local files, analyze_video_in_session for existing sessions) or provide when-not 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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