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felipefontoura

YouTube MCP Server

youtube_analytics_day_of_week

Return the response.

Instructions

Get aggregated performance by day of week.

Fetches daily data and aggregates by weekday to show which days perform best. Useful for scheduling uploads.

Args: start_date: Start date (YYYY-MM-DD). Defaults to 90 days ago. end_date: End date (YYYY-MM-DD). Defaults to today.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_dateNo
start_dateNo
Behavior3/5

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 discloses that it 'Fetches daily data and aggregates by weekday,' which is a meaningful behavioral trait. However, it doesn't describe the output format, whether auth is required (though siblings suggest youtube_auth), pagination behavior, or performance implications of fetching 90 days of data. Reasonable but not comprehensive.

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: a two-sentence purpose, one-line usage context, and an Args block documenting both parameters. It's appropriately front-loaded with the core purpose first. The Args section is slightly redundant with the description's format mention but is standard formatting. No wasted words.

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 read-only analytics aggregation tool with 2 optional parameters and no output schema, the description covers the essential purpose, defaults, and an example use case. However, it doesn't explain what metrics are included in the aggregation (views? watch time? likes?), which is material since the tool name says only 'performance' generically. It also lacks details on whether the output distinguishes active/upload days.

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%, meaning the schema has no descriptions for start_date or end_date. The description does provide some parameter context in the Args block: both default behaviors are stated (90 days ago, today) and the YYYY-MM-DD format is given. This adds real value beyond the bare schema, though the description covers only 2 parameters (which is all there are). Baseline 3 is appropriate since it compensates for the 0% schema coverage.

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 states a clear purpose: 'Get aggregated performance by day of week,' with a specific verb (get) and resource (aggregated analytics by weekday). It differentiates from sibling analytics tools with distinct dimensions (top_videos, traffic_sources, demographics), though the mention of day-of-week distinguishes it primarily by aggregation dimension rather than naming specific siblings.

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 includes 'Useful for scheduling uploads,' which gives clear context for when to use this tool. However, it doesn't explicitly state when NOT to use it or name alternative tools (e.g., youtube_analytics_daily for raw daily data, or youtube_analytics_overview for high-level metrics). No exclusions or alternatives are provided.

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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