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krita-mcp

krita-mcp

by jowinjohnchemban
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

modify_selection

Change an active selection by inverting, growing, shrinking, feathering, adding a border, or smoothing its edges, using a pixel amount for the adjustment.

Instructions

operation: invert, grow, shrink, feather, border or smooth. amount in pixels.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "operation": "<operation>"
    },
    "name": "modify_selection"
  }
}

Input Schema

NameRequiredDescriptionDefault
amountNo
operationYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

C2.9/5.0
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 does not state whether the operation mutates the active selection, whether changes are undoable, how amount affects each operation, or what happens when no selection exists.

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?

The definition is compact and front-loads the operation choices. However, the fragmentary phrasing is terse to the point of omitting a clear subject and verb.

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 a mutation tool with no annotations, no output schema, and zero schema description coverage, the description is too sparse. An agent still lacks essential context about selection state requirements and the effect of each operation.

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 0%, so the description must compensate. It usefully enumerates operation values and says amount is in pixels, but it does not clarify which operations use amount, what the default means, or constraints on the values.

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 lists the specific selection-modification operations (invert, grow, shrink, feather, border, smooth), so the tool's purpose is inferable with the name. It does not explicitly state that it modifies the active selection or distinguish it from siblings like set_selection or fill_selection.

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?

The description names possible operations but gives no guidance on when to use this tool versus set_selection, fill_selection, or export_selection_mask. It also omits prerequisites such as whether an active selection must exist.

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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