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Nexscope Ecommerce Data MCP

Smart Multi-Image Editing API v3

nexscope_smart_multi_image_editing_v3

Create an edited output from multiple source images using prompt, provider, resolution, and quality controls.

Input Schema

NameRequiredDescriptionDefault
promptNoOptional fusion instruction, up to 600 characters.
qualityNoGPT Image quality only. Supported values: low, medium, or high. Defaults to medium.
providerYesImage model. Supported values: BANANA, BANANA_2, BANANA_PRO, WAN2_7, QWEN_IMAGE_3_PRO, SEEDREAM5, GPT_2_IMAGE, or AIDRAW_EDIT.
templateNoOptional fusion template. Supported values: outfit-fusion, outfit-try-on.
imageListYesPublic image URLs to combine or reference. Provide no more than 6 JPG, JPEG, PNG, or WEBP images; each image must be at most 10 MB and between 800 and 4096 pixels.
outputNumNoNumber of images to generate. Defaults to 1.
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

C2.9/5.0
Behavior2/5

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

Annotations declare readOnlyHint=false and openWorldHint=true, and the description's 'Create' is consistent with that. Beyond this, it adds nothing: no mention of cost, latency, whether the operation is async and needs nexscope_media_task_result polling, or what the caller receives. For a paid, open-world image generation call this is a meaningful gap.

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 well-formed sentence with the verb front-loaded and no filler. It is appropriately sized, though its brevity comes partly from omitting information rather than from disciplined compression.

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?

Ten parameters, no output schema, and an open-world generation annotation mean the description carries real burden. It says nothing about how the result is returned or retrieved, how provider choice affects output, or what the fusion templates do, so an agent cannot confidently invoke this correctly on description alone.

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 100%, so the schema already documents all 10 parameters including the provider enum, image constraints, quality values, and templates. The description merely echoes 'prompt, provider, resolution, and quality controls' and adds no semantics beyond the schema, which matches the baseline 3 for high-coverage schemas.

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?

States a specific verb and resource: 'Create an edited output from multiple source images.' The 'multiple source images' wording plausibly distinguishes it from single-image siblings like nexscope_smart_image_edit_manipulation_v3 or nexscope_image_inpainting, but no sibling is named, so the differentiation is inferred rather than explicit.

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 guidance on when to pick this tool over nexscope_smart_image_edit_manipulation_v3, nexscope_smart_image_outpainting, or the many single-provider generation tools. No exclusions, no prerequisites, no note about which provider to choose for which scenario.

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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