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Hanyuyu

ImgLume MCP

by Hanyuyu

generate_image

Generate an image from a text prompt or edit an existing image by providing its URL or local path and describing the change.

Instructions

Generate or edit one image with ImgLume. For edits, pass the source image URL or local file path in referenceImages and keep the prompt focused on the requested change. Omit model, quality, or aspectRatio to use live ImgLume defaults.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoOptional model ID
promptYesImage generation prompt
qualityNoOptional quality value
promptIdNoOptional ID returned by get_inspiration
aspectRatioNoOptional ratio such as 1:1, 16:9, or 9:16
referenceImagesNoPublic image URLs or absolute/local image file paths
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It discloses the tool can generate or edit, but it does not mention return format (e.g., image URL or file path), error handling, rate limits, or potential side effects. This is a significant gap for a tool that produces output.

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 a single, dense sentence with no redundancy. It front-loads the main action and immediately provides usage tips. Every phrase adds value, achieving maximum conciseness without sacrificing clarity.

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?

Given the complexity (6 parameters, no output schema, no annotations), the description is adequate for basic usage but lacks important details such as output format, error handling, or processing time. A more complete description would include what the tool returns or how to handle failures.

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%, but the description adds meaningful context: referenceImages should contain source file for edits, and prompt should focus on the change. It also suggests omitting certain parameters to use defaults, which enhances understanding beyond the schema definitions.

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 'Generate or edit one image with ImgLume', specifying the verb (generate/edit) and resource (image). It distinguishes from sibling tools like generate_video (video) and search_gallery (searching), establishing a unique purpose.

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 explicit guidance for editing: pass source image in referenceImages and keep prompt focused. It also advises omitting model, quality, aspectRatio to use defaults. While it doesn't explicitly state when not to use the tool, the context is clear for typical usage.

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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