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youtube_analytics_traffic_sources

Discover where YouTube views originate by analyzing traffic sources like search, suggested, browse, and external, with options to filter by date range or specific video.

Instructions

Get traffic source breakdown — how viewers find your content.

Shows views from search, suggested, browse, external, etc.

Args: start_date: Start date (YYYY-MM-DD). Defaults to 28 days ago. end_date: End date (YYYY-MM-DD). Defaults to today. video_id: Optional video ID to filter to a specific video.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_dateNo
video_idNo
start_dateNo
Behavior3/5

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

With no annotations, the description carries the full burden for behavioral disclosure. It does explain that the tool returns views by traffic source, but it does not mention required authentication, data granularity, limitations, or response format. This is adequate but leaves 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 concise and well-structured: a one-sentence summary, a supplementary line about content, and a clean args list. No fluff, and the main purpose is front-loaded.

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 tool is simple with three optional parameters and no output schema. The description covers the purpose and parameters well, though it does not detail the exact output structure or metrics beyond 'views'. Overall it is reasonably complete for the tool's complexity.

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?

All three parameters (start_date, end_date, video_id) are described with formats, defaults, and optionality, which is valuable given the schema has no per-parameter descriptions. This adds meaning beyond the raw 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 function with a specific verb 'Get' and resource 'traffic source breakdown'. It lists example traffic sources (search, suggested, browse, external) and distinguishes it from sibling analytics tools like demographics or geography.

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 for analyzing how viewers discover content, but does not explicitly state when to use it over other analytics tools or mention any exclusions. No alternative tools are named, so guidance is only implicit.

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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