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labeveryday

GPT Image MCP Server

by labeveryday

generate_reference_thumbnail

Generate YouTube thumbnails from a reference image using a standard layout with main text, optional red banner text, topic, and composition style settings.

Instructions

SPECIALIZED tool for YouTube thumbnails using reference images with predefined layouts.

Use this tool specifically for YouTube thumbnails when you want the standard thumbnail layout (person on right, text on left, red banner) with a reference image. For other content types or custom layouts with reference images, use the general generate_image tool instead.

Args: reference_image: Reference image - must be either a file path (e.g., "/path/to/image.jpg") or base64 encoded image data. Claude's "[Image #1]" format is not supported - save the image to a file first. main_text: Main headline text for the thumbnail secondary_text: Optional secondary text for the red banner topic: Topic or subject matter (e.g., 'tech side hustles', 'AWS certification') style_override: Optional style override for different thumbnail types creative_mode: Enable creative freedom vs. consistent branding (default: False) composition_style: Composition approach (centered, left, right, dynamic, creative) layout_freedom: Layout constraints (standard=branding, flexible=some creativity, experimental=full freedom)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNo
main_textYes
creative_modeNo
layout_freedomNostandard
secondary_textNo
style_overrideNo
reference_imageYes
composition_styleNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

The description discloses a key behavioral constraint: reference_image cannot use Claude's '[Image #1]' format and must be a file path or base64 data. It also explains the meaning of layout_freedom values (standard, flexible, experimental), adding value beyond the annotations (which are absent).

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 structured with a bolded intro, usage guidance, and an args list. Each arg line is compact yet informative, with no filler. The length is justified by the tool's eight parameters.

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 the tool's complexity (8 parameters, no schema descriptions, no annotations), this description covers purpose, usage, parameter semantics, and constraints. The existence of an output schema means return values need not be explained, so no gaps are apparent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description compensates by explaining all 8 parameters. For example, it clarifies that reference_image must be a file path or base64, and that layout_freedom maps to branding constraints. It provides examples for topic and lists options for composition_style.

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 identifies the tool as a specialized YouTube thumbnail generator using reference images and predefined layouts, and it distinguishes itself from the general generate_image tool by mentioning the standard thumbnail layout. The 'person on right, text on left, red banner' detail provides concrete context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool (for YouTube thumbnails with the standard layout) and when to use generate_image instead (other content types or custom layouts), giving clear decision criteria.

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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