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felipefontoura

YouTube MCP Server

youtube_analytics_traffic_sources

Get a breakdown of how viewers discover your YouTube videos, showing views from search, suggested, browse, external, and other sources. Filter by date range or a 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
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It doesn't disclose that this is a read-only safe operation, whether it requires auth (there's a youtube_auth sibling), whether it needs a channel ID, date-range limits, or what the return format looks like. For a data-pull tool with zero annotation coverage, more behavioral context is needed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded with the core purpose sentence, followed by a brief elaboration and a clear Args section. It's efficient with no wasted sentences, though the Args section partially restates schema parameter titles at a basic level.

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?

For a tool with no output schema and no annotations, the description provides the core purpose but omits the return structure, whether it needs a channel/account selected, and any prerequisites (e.g., auth). The tool complexity is moderate (analytics query with 3 optional params), so the description is adequate but leaves gaps around output shape and setup requirements.

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 description coverage is 0%, so the description must compensate. It does explain start_date and end_date defaults (28 days ago / today) and video_id as an optional filter, which adds real meaning beyond the schema. However, it doesn't note that start_date and end_date are mutually required, what format errors might occur, or whether video_id requires a specific scope.

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 gets a traffic source breakdown for how viewers find content, listing example sources (search, suggested, browse, external). This clearly distinguishes it from sibling analytics tools like demographics, geography, and retention. However, it doesn't explicitly contrast against its closest sibling youtube_analytics_overview to differentiate scoping.

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 (get traffic source breakdown) but gives no explicit guidance on when to use this vs alternatives like youtube_analytics_overview or youtube_analytics_top_videos. It doesn't state when NOT to use it or which sibling is better suited for different analytic questions.

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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