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tuitamogamer-gpt

youtube-mcp-server

by tuitamogamer-gpt
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TypeScript
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Channel Analytics Summary

youtube_channel_summary
Read-onlyIdempotent

Retrieve a performance summary for your YouTube channel showing views, watch time, subscriber changes, likes, and more. Optionally breakdown data by day or month.

Instructions

Retrieve a broad performance summary for the authenticated channel covering views, watch time, subscriber changes, likes, dislikes, comments, and shares. Optionally break the data down by day or month.

Args:

  • startDate (optional): Inclusive start date in YYYY-MM-DD format. Defaults to 28 days ago.

  • endDate (optional): Inclusive end date in YYYY-MM-DD format. Defaults to today.

  • dimension (optional): Time grouping — "none" (default, aggregate totals), "day" (one row per day), or "month" (one row per month).

  • response_format (optional): "markdown" (default) or "json".

Returns (JSON shape):

{
  "columns": ["views", "estimatedMinutesWatched", "averageViewDuration", "averageViewPercentage",
               "subscribersGained", "subscribersLost", "likes", "dislikes", "comments", "shares"],
  "rows": [[12345, 67890, 240, 45.2, 100, 10, 500, 20, 80, 30]]
}

When dimension is "day" or "month", the first column is the date/month string.

Examples:

  • "Give me my channel stats for last month" → pass startDate / endDate covering that month.

  • "Daily breakdown of my channel this week" → dimension: "day" with appropriate dates.

Errors:

  • 403: insufficient scope — re-run npm run auth.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
startDateNoInclusive start date in YYYY-MM-DD format. Defaults to 28 days ago.
endDateNoInclusive end date in YYYY-MM-DD format. Defaults to today.
dimensionNoTime grouping: "none" (default) for aggregate totals, "day" for per-day rows, "month" for per-month rows.none
response_formatNoOutput format: "markdown" (default) for a human-readable table, "json" for the structured payload.markdown

Tool Definition Quality

A4.4/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds valuable behavioral context: the JSON shape of the response, error handling (403 scope), and the effect of the dimension parameter on output structure. It does not contradict annotations. The added detail on default date range and format enhances transparency.

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 well-structured with sections for description, arguments, returns, examples, and errors. It is not overly verbose for the amount of detail provided. Every sentence adds value. However, it could be slightly more concise; some details about default behavior are repeated in both description and schema.

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

Completeness5/5

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

Given no output schema, the description compensates by providing the exact JSON shape and explaining the markdown output. It covers error handling (403), includes examples, and explains optional parameters with defaults. The tool is well-documented for an agent to use correctly.

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 coverage is 100%, so baseline is 3. The description adds meaning beyond the schema by providing usage examples (e.g., 'Daily breakdown of my channel this week'), explaining the effect of dimension on output, and clarifying default behavior. The error note also adds context. This elevates the score above baseline.

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 retrieves a 'broad performance summary' for the authenticated channel, listing specific metrics. The verb 'Retrieve' and resource 'channel performance summary' are precise. Among siblings, this is distinct from query-based analytics (youtube_run_analytics_query) and video-specific tools (youtube_top_videos, youtube_video_performance).

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?

The description provides guidance on when to use the tool (for channel summary), includes optional parameters with defaults, and gives examples. It does not explicitly state when not to use it or suggest alternatives, but the examples and error note indirectly guide usage. A slightly stronger score would require explicit exclusions.

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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