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SekaiNoOwari77

mcp-3d-modeling-agent

blender_msfs_livery_set_paint_brush

Configure paint brush settings for MSFS liveries: choose from presets like soft airbrush, hard edge, detail, smudge, clone, or fill, and adjust size, color, and strength.

Instructions

Configure paint brush settings with presets (soft_airbrush, hard_edge, detail_brush, smudge, clone, fill)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNoBrush size in pixels
colorNoRGBA paint color (0-1 range)
presetNoBrush preset name
strengthNoBrush strength (0-1)

Schema Changelog

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

  1. First observedv0.4.0

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure, but it only says 'Configure paint brush settings' and does not explain side effects, persistence, whether it requires active paint mode, or whether it resets other brush properties. The listed presets provide some useful detail, but mutation semantics and any operational constraints are unstated.

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?

The description is a single efficient sentence that front-loads the core action and then adds the most useful non-schema information. There is no filler, repetition, or clutter.

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 tool with no annotations, no output schema, and a workflow-specific MSFS livery context, the description is too thin. It does not explain how brush settings interact with the livery painting workflow, whether paint mode must already be active, or what the expected result is. An agent would need to infer too much from the name and sibling list.

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?

The input schema already describes all four parameters with 100% coverage, so the baseline is 3. The description adds value by enumerating concrete preset values (soft_airbrush, hard_edge, detail_brush, smudge, clone, fill) that the schema's generic 'Brush preset name' does not provide, which materially helps an agent pick valid inputs.

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 states a specific verb ('Configure') and a clear resource ('paint brush settings'), and lists concrete preset names, which helps an agent understand the tool's intent. It is distinguishable from siblings like sample_color or get_paint_presets by focusing on configuration rather than querying or sampling. It stops short of explicitly contrasting with those siblings, so it does not earn a 5.

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 gives no guidance on when to use this tool versus sibling tools such as blender_msfs_livery_setup_paint_mode or blender_msfs_livery_get_paint_presets. There is no mention of prerequisites like entering paint mode first, nor any indication that get_paint_presets should be used to discover valid presets. Context must be inferred entirely from the tool name.

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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