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Nexscope Ecommerce Data MCP

Smart Image Edit & Manipulation API v3

nexscope_smart_image_edit_manipulation_v3

Perform general image editing with provider, prompt, resolution, aspect ratio, and quality controls.

Input Schema

NameRequiredDescriptionDefault
promptYesEditing instruction.
sourceNoOptional traffic or product source code.
qualityNoGPT Image quality only. Supported values: low, medium, or high. Defaults to medium.
imageUrlYesPublic URL of the image to edit. The image must be between 300 and 4096 pixels in both width and height, and its width-to-height ratio must be between 0.4 and 2.5.
providerYesImage model. Supported values: BANANA, BANANA_2, BANANA_PRO, WAN2_7, QWEN_IMAGE_3_PRO, SEEDREAM5, GPT_2_IMAGE, or AIDRAW_EDIT.
templateNoOptional Nexscope editing template. Supported values: white-background, product-main-image-retouching, scene-generation, poster-design, add-person-or-object, change-animal, flat-lay-apparel, 3d-apparel, mannequin-to-model, cartoon-illustration, body-reshape, change-style, remove-element, remove-text, remove-watermark, add-watermark.
outputNumNoNumber of images to generate, from 1 to 4.
resolutionNoTarget resolution preset.
supplyTypeNoGeneration route. Supported values: eco or stable. Defaults to stable.
aspectRatioNoTarget aspect ratio.
needOptimizeNoWhether the prompt should be optimized upstream.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.6/5.0
Behavior2/5

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

Annotations declare readOnlyHint=false and openWorldHint=true, so the agent knows this mutates state and reaches external models. The description adds nothing beyond that: it doesn't mention that calls are generation jobs (likely async/costly), how to retrieve results, or provider-specific constraints like quality applying only to GPT Image. For an 11-param generative mutation, this is thin.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single efficient sentence with the action front-loaded and no wasted clauses. It is concise but borders on under-specification rather than padding.

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

Completeness2/5

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

For an 11-parameter generative editing tool with no output schema, the description omits critical context: result handling, whether operations are async, cost/latency implications, and the role of Nexscope-specific params like template and needOptimize. Only the annotations carry behavioral signal, leaving the description incomplete.

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 schema already documents every parameter including the provider enum, template values, and imageUrl size constraints. The description merely recites a subset of parameter names (provider, prompt, resolution, aspect ratio, quality), adding no meaning beyond the schema — the baseline 3 applies.

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

Purpose3/5

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

States a specific verb and resource ("Perform general image editing") but "general" leaves the scope fuzzy against a large family of sibling image tools like nexscope_smart_multi_image_editing_v3, nexscope_image_inpainting, nexscope_object_eraser_image_object_removal, or nexscope_one_click_image_recoloring_v2. No differentiation is offered, so an agent cannot tell from the description alone which image-edit tool to pick.

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 statement of when to use this tool, when not to, or what alternatives exist. With dozens of sibling editing/generation tools, the absence of routing guidance is a real gap; the description only names controls, not conditions.

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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