magnific_images_upscale
AI upscale 2x/4x (Magnific, premium). Exact pixels: images_resize. Aspect: images_crop. Default scale=2.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| scale | No | ||
| folderReference | No | ||
| creationIdentifier | Yes |
AI upscale 2x/4x (Magnific, premium). Exact pixels: images_resize. Aspect: images_crop. Default scale=2.
| Name | Required | Description | Default |
|---|---|---|---|
| scale | No | ||
| folderReference | No | ||
| creationIdentifier | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are all false, so they don't convey much. The description adds 'premium' and 'AI' context, implying a paid AI service, and states 'Default scale=2' which is a behavioral default. However, it does not disclose whether the operation is synchronous, if it modifies the original, or what output is produced. This is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: a single sentence with key information front-loaded. It states the main purpose, alternatives, and default in under 20 words. No fluff, every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no output schema and no annotation guidance, the description should at least hint at outcome or side effects. It mentions 'premium' suggesting cost, and alternatives for other operations, but it does not describe what the tool returns (e.g., a new creation ID) or whether it modifies existing images. For a simple 3-parameter tool, this might be sufficient, but the lack of output/behavior details leaves gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must illuminate the parameters. It mentions '2x/4x' aligning with the scale enum and 'Default scale=2' which clarifies the scale parameter's default. However, it provides no explanation for creationIdentifier (though self-evident) or folderReference, leaving these ambiguous, especially folderReference which is not obvious. The description only partially compensates for missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'AI upscale 2x/4x' with specific scale options. It distinguishes from siblings by explicitly pointing to alternatives for exact pixel resizing (images_resize) and aspect ratio changes (images_crop), making the tool's unique purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance by comparing with alternative tools: 'Exact pixels: images_resize. Aspect: images_crop.' This tells the agent when to choose this tool over others. It also notes the default scale, giving a concrete parameter default. This is strong guidance for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.