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tuitamogamer-gpt

youtube-mcp-server

Set Video Thumbnail

youtube_set_thumbnail

Set a custom thumbnail for a YouTube video by uploading a local image file. Accepts PNG, JPG, GIF, and BMP formats up to 2 MB.

Instructions

Upload and set a custom thumbnail for a video.

The image is streamed from a local file. The MIME type is inferred from the file extension (.png, .jpg/.jpeg, .gif, .bmp).

Args

  • videoId (string, required): video to update the thumbnail for

  • imagePath (string, required): absolute path to the local image file

Returns Short confirmation + thumbnail resource with URLs for all size variants.

Examples

  • Set thumbnail: { "videoId": "abc123", "imagePath": "/tmp/thumb.jpg" }

Errors

  • 400: file not found, unsupported format, or image too large (max 2 MB)

  • 403: thumbnails require a verified channel or custom thumbnail permission

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
videoIdYesID of the video to set the thumbnail for.
imagePathYesAbsolute path to the local image file (.png, .jpg, .jpeg, .gif, .bmp).
Behavior4/5

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

The description discloses file streaming behavior, MIME type inference, allowed formats, max file size (2 MB), and error conditions. Annotations already indicate non-destructive nature, but the description adds operational details beyond annotations.

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 well-structured with clear sections (Args, Returns, Examples, Errors). It is concise, with every sentence adding value—no redundancy or irrelevant content.

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?

For a tool with 2 parameters and no output schema, the description covers purpose, usage, parameters, return format (confirmation + thumbnail resource with URLs), examples, and error conditions. It meets the needs of an AI agent selecting and invoking the tool.

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 descriptions already cover both parameters. The description adds context (e.g., absolute path requirement, file extensions) and ties parameters to error conditions (file not found, unsupported format). Schema coverage is 100%, so baseline is 3; the extra context pushes it to 4.

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 'Upload and set a custom thumbnail for a video,' which is a specific verb and resource. It distinguishes from sibling tools like youtube_upload_video (uploads video) and youtube_update_video (updates video metadata) by focusing on thumbnail operations.

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 context through examples and error conditions, but does not explicitly state when to use this tool over alternatives. It is clear for the intended use case, but lacks explicit when-not-to-use guidance.

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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