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gimp-mcp-studio
by Onru-Labs

select_by_color

Select image regions by color similarity using a target color and tolerance threshold, with replace, add, subtract, or intersect operations to refine selections.

Instructions

Select regions by color similarity.

Parameters:

  • color: Target color as CSS name, hex (#rrggbb), or rgb() string

  • threshold: Color similarity tolerance 0-255 (default 15)

  • operation: "replace" (default), "add", "subtract", "intersect"

  • image_index: Target image index (default 0)

  • layer_name: Layer to sample from; defaults to active layer

Returns status dict.

Input Schema

NameRequiredDescriptionDefault
colorYes
operationNoreplace
thresholdNo
layer_nameNo
image_indexNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full behavioral burden. It reveals that the return is a 'status dict' and that selection mode is controlled by operation (default 'replace'), but says nothing about failure conditions, effect on the previous selection for non-replace modes, undo behavior, or the shape of the returned dict.

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?

One-sentence purpose followed by a compact parameter table — every line adds information an agent needs, and the purpose is front-loaded before the details. No filler or repetition.

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?

With no annotations and no output schema, the description is only just adequate: it documents all five parameters well but leaves the return value as an opaque 'status dict' and omits error behavior and interaction with an existing selection. For a selection-mutating tool that is a meaningful gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, and it does: it documents accepted color formats (CSS name, hex, rgb()), the 0-255 range and default of threshold, the enumeration of operation values, and that layer_name falls back to the active layer. Only image_index gets a bare restatement with no added meaning.

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 opens with a specific verb+resource: 'Select regions by color similarity,' which clearly separates it from the geometric siblings (select_rectangle, select_ellipse) and from select_all/select_none. It does not explicitly name an alternative tool, but the operation is unambiguous.

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 prefer this over other selection tools, no prerequisites (e.g., an image must be open), and no guidance on choosing a threshold value. The operation list implies the modes but never explains when to use 'add' versus 'replace' in a workflow.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.