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Nexscope Ecommerce Data MCP

Image Text Editing API

nexscope_image_text_editing

Use an image mask to remove or edit text regions in an ecommerce image.

Input Schema

NameRequiredDescriptionDefault
imageUrlYesPublic URL of the base image.
imageMaskUrlYesPublic URL of the text mask image.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.8/5.0
Behavior2/5

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

Annotations already say readOnlyHint=false and openWorldHint=true, so the agent knows this mutates state over the network, but the description adds nothing beyond that: no statement of processing latency, no explanation of what the mask should look like (white-on-black vs alpha), and no mention of whether removed text is inpainted or left blank. For a mutating generative tool with no output schema, this is a real gap.

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

Conciseness3/5

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

A single front-loaded sentence with zero filler, but the brevity comes at the cost of under-specification rather than efficient compression. Nothing is redundant, yet almost nothing beyond the mechanics of masking is conveyed.

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?

No output schema, no meaningful annotations about effect, and only one sentence of description for a generative image-mutation tool. An agent cannot tell what comes back (an image URL?), how long it takes, or how to construct a valid mask, all of which it must know to call this correctly.

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 both parameters are documented as public URLs, giving a baseline of 3. The description's only added signal is that one URL is an 'image mask' applied to text regions, which the schema already says; it does not specify mask polarity, resolution, or format requirements that commonly break this kind of call.

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 names a specific verb pair (remove or edit text regions) and a specific resource (text regions in an ecommerce image), plus the mechanism (an image mask). It is distinguishable from sibling image tools like nexscope_image_translation or nexscope_object_eraser_image_object_removal, though the 'edit' half is never defined and implies a replacement-text capability the schema does not expose.

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?

No guidance on when to choose this over the many adjacent siblings (nexscope_image_inpainting, nexscope_smart_image_edit_manipulation_v3, nexscope_product_logo_detection_removal, nexscope_image_translation). The only implicit condition is that the caller must already have a text mask, which is never stated as a prerequisite or exclusion.

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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