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recraft_erase_region

Remove unwanted objects from images by applying a mask; the erased area is filled naturally with surrounding content.

Instructions

Content-aware removal of a region in an image using a mask. White mask areas are erased and filled naturally.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYesLocal path to source image (max 4MP)
mask_pathYesLocal path to mask (white=erase, black=preserve, same dimensions)
response_formatNoResponse formaturl

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.2.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It usefully explains that white mask areas are removed and content-aware filled, but it does not state whether the source file is mutated, what kind of output is returned, or any side effects or limitations beyond the schema.

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 short sentences with the core operation front-loaded and a clarifying behavioral detail in the second sentence. There is no filler or redundant structure.

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

Completeness3/5

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

The core mask behavior is covered, and the schema handles parameter documentation, but with no annotations and no output schema, the description does not disclose output format behavior, source-file mutation, or how this tool differs from overlapping siblings. It is minimally complete but has clear gaps.

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?

The schema already documents all three parameters at 100% coverage, so the baseline is 3. The description adds 'White mask areas are erased and filled naturally,' which reinforces mask_path semantics, but it does not add meaningful parameter-level information beyond what the schema already provides.

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 ('erase'), a resource ('region in an image'), and a mechanism ('using a mask'), and clarifies that white mask areas are removed and filled naturally. It is clear on its own, but it does not explicitly distinguish this tool from the sibling recraft_inpaint or from the other removal/editing tools.

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 use erase_region versus recraft_inpaint, recraft_remove_background, or recraft_outpaint. The mask semantics imply a use case, but no when/when-not criteria or alternative routing is provided.

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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