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Xenition

Edit an image

edit_image

Use this when the user wants an existing image changed: edit it by instruction, upscale, remove the background, enhance, erase something, restyle, colorize, restore, expand the canvas, or make a variation. Saves the result as a new image in their Xenition library; the original is kept.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imageYeshttps URL of the image to edit (e.g. from create_image)
titleNo
promptNowhat to change, for edit / erase / stylize
operationYesone of: edit, upscale, background-removal, enhance, erase, stylize, colorize, restore, expand, variation

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNo
kindNo
errorNo
titleYes
statusYes
openUrlNo
artifactIdNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare destructiveHint=false and readOnlyHint=false, and the description usefully adds that the result is saved as a new image while the original is kept – reinforcing non-destructiveness and clarifying output location. It doesn't cover permissions or rate limits, but it earns real credit beyond the 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?

Two sentences, front-loaded with the trigger and operations, then the output behavior. No filler; every clause carries weight.

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?

With an output schema present, return values need no explanation, and the description still confirms the saved-result location. The only real gap is prerequisites (auth or library context), but for a mutation tool with annotations this is largely complete.

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 coverage is 75%, so the schema already documents image, prompt, and operation values. The description's operation list loosely mirrors the enum but adds no syntax or format detail beyond what the schema provides. Baseline 3 is appropriate.

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?

Specific verb (edit) plus resource (image), with a full enumeration of operations that mirrors the operation param and distinguishes it from the sibling create_image by scoping to an 'existing image'. An agent can tell what this does without opening the schema.

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 opening clause 'Use this when the user wants an existing image changed' gives clear triggering context, and the operation list clarifies the breadth of edits. It stops short of naming alternatives (e.g., create_image) or stating when-not-to-use, so it's clear but not complete.

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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