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Upscale an image

luw_upscale_image

Luw.ai Photo Enhance AI: enhance the quality of an image and enlarge it 2x, 4x or 8x. Costs 1 credit.

Instructions

Luw.ai Photo Enhance AI: enhance the quality of an image and enlarge it 2x, 4x or 8x. Costs 1 credit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imageYesImage to upscale (https:// URL, local file path, or data: URI).
scaleNo2, 4 or 8 (default 2).
formatNoOutput image format.
precisionNoHow strictly to keep the input's structure: 90 = precise, 75 = balanced, 40 = creative.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.3.2

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, idempotentHint=false, openWorldHint=true and destructiveHint=false, so the safety profile is largely covered. The description adds genuinely new behavior in stating the 1-credit cost, but says nothing about auth, result retrieval, or failure behavior.

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?

Two compact sentences with the capability statement first and the cost constraint second. No filler, no repetition; every clause carries information an agent can use.

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?

For a simple generation tool whose annotations cover the safety profile and whose schema is fully documented, the description is nearly adequate. However, the presence of luw_get_result among siblings suggests generation is asynchronous, and the description never mentions how or where the upscaled image is retrieved.

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

Parameters3/5

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

Schema description coverage is 100%, so all four parameters (image, scale, format, precision) are already documented with defaults, valid values and meanings. The description restates the scale values, adding nothing the schema does not already contain; baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific verb and resource — enhance/enlarge an image — with the concrete scale options (2x, 4x, 8x). It never distinguishes itself from close siblings like luw_edit_image or luw_vectorize_image, which also take an image and return a transformed image, so the agent must infer the difference.

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?

There is no when-to-use or when-not-to-use guidance and no alternative named, despite many image-manipulation siblings. The only decision-relevant context offered is the 1-credit cost, which helps but does not tell the agent how to choose this tool over its neighbors.

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