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Edit image with a prompt (Magic Prompt AI)

luw_edit_image

Edit images with plain-language prompts to recolor objects, add furnishings, or change scenes. Supply reference images to place products or apply materials.

Instructions

Edit any image with a plain-language instruction: "make the sofa green velvet", "add a pendant lamp over the table", "turn it into a night scene". Pass products, materials or a mood board as reference_images to place or apply them. For edits restricted to an exact area, use luw_magic_wand. Costs 1 credit per variation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNoFix for reproducible results.
imageYesImage to edit (https:// URL, local file path, or data: URI).
engineNoModel: aria (default), symphony (Symphony-3) or nano-banana-2.
formatNoOutput image format.
promptYesThe edit to make.
resolutionNoOutput resolution (default 2k).
variationsNoNumber of alternative designs (1-4, default 1); each is billed as a generation.
enhance_promptNoLet Luw.ai's prompt enhancer expand a short prompt.
reference_imagesNoUp to 6 reference images (furniture, materials, products, mood boards) to draw from.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover the safety profile (not read-only, not idempotent, open-world, not destructive), so the bar is lower. The description adds genuinely useful context beyond that: the cost model ("1 credit per variation") which is not in the schema or annotations. It does not describe failure behavior or output form, keeping it at a 4.

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?

Three tight sentences, front-loaded with the purpose and examples, then the reference_images note, the alternative routing, and the cost fact. No filler or 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?

For a 9-parameter generation tool the description covers purpose, references, alternative routing, and cost. Since there is no output schema, it could have clarified what is returned (image URL/artifact, variation handling) and what happens on failure, which is the only notable gap.

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 the baseline is 3. The description elaborates the intent of reference_images (place/apply products or materials) and gives example prompts, but it adds no syntax, format, or constraint detail beyond what the schema already documents for the 9 parameters.

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?

Starts with a specific verb+resource ("Edit any image") plus the mechanism (plain-language instruction) and concrete prompt examples. It also positively distinguishes itself from luw_magic_wand for area-restricted edits, so an agent can separate it from that sibling without reading schemas.

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?

It states the core use case, explains reference_images usage (products, materials, mood board), and routes precise area edits to luw_magic_wand. It lacks guidance versus other siblings like luw_generate_image (no source image) or the design-specific tools, so context is clear but exclusions are partial.

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