Skip to main content
Glama

upscale_image

Idempotent

Upscale images to custom resolutions (up to 128 MP) with optional detail and realism enhancement. Choose output format from webp, jpg, or png.

Instructions

Upscale an image using Pruna AI.

Args: image: Image URL or local file path to upscale target: Target resolution in megapixels (1-128, capped at 128 MP) output_format: Output format (webp, jpg, png) enhance_details: Enhance fine textures enhance_realism: Improve realism (recommended for AI-generated images)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imageYes
targetNo
output_formatNojpg
enhance_detailsNo
enhance_realismNo
Behavior3/5

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

Annotations already provide readOnlyHint=false (mutation), destructiveHint=false, and idempotentHint=true. The description adds that it upsamples and enhances details/realism but does not reveal additional behavioral traits like file size limits or processing time. It meets the baseline but adds minimal value 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?

Extremely concise: one-line purpose followed by a clear bullet list of parameters. Every sentence is necessary and front-loaded, with no redundancy.

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

Completeness4/5

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

The description covers all input parameters but omits details about the output (e.g., returned image URL). Given the tool's moderate complexity and lack of output schema, describing the return value would improve completeness.

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 fully explains each parameter: image source, target megapixels with range, output format options, and boolean enhancements. This adds crucial meaning beyond the schema's type/defaults, enabling correct usage.

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's action: 'Upscale an image using Pruna AI.' This directly conveys the purpose, distinguishing it from sibling tools like edit_image and generate_image.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool versus alternatives. It does not mention any prerequisites or situations where the tool is inappropriate, leaving the agent to infer usage from the parameter descriptions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/charlesrapp/pruna-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server