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Blender Copilot MCP Server

by dwgx

cloth_sim_model

Simulate cloth physics to drape fabric naturally on meshes like skirts or capes, defining pin points and adjusting stiffness, damping, and gravity.

Instructions

Run cloth simulation for modeling purposes (e.g., draping fabric).

Simulates cloth physics and applies the result to the mesh. Useful for creating natural fabric drapes, cape rest poses, or skirt shapes.

Args: mesh_name: Name of the mesh to simulate. pin_vertex_group: Vertex group for pinned vertices (e.g., waist for skirt). frames: Number of frames to simulate. quality: Simulation quality steps per frame. gravity: Gravity strength (negative = downward). stiffness: Cloth structural stiffness. damping: Cloth damping.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
framesNo
dampingNo
gravityNo
qualityNo
mesh_nameYes
stiffnessNo
pin_vertex_groupNo
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. It states the tool 'applies the result to the mesh' but does not disclose whether the modification is destructive, if undo is supported, or if baking is required. Lacks details on performance impact or blocking behavior.

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 description is concise with a clear header paragraph followed by well-structured parameter descriptions. Every sentence is useful, though the 'Args' list could be integrated more naturally. Overall, it is efficiently written without unnecessary verbiage.

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?

Given the complexity of cloth simulation and the absence of an output schema, the description is incomplete. It does not explain what 'applies the result to the mesh' entails (e.g., modifies vertices, creates shape keys) or mention required preconditions like an existing cloth modifier. The lack of behavioral context limits its usefulness for an AI agent.

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?

Although schema description coverage is 0%, the description includes an 'Args' section that explains each parameter's role (e.g., 'pin_vertex_group: Vertex group for pinned vertices'). This adds significant meaning beyond the bare schema names and defaults, compensating for the lack of schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool runs a cloth simulation for modeling purposes, with specific examples of draping fabric, cape rest poses, or skirt shapes. It distinguishes itself from sibling tools like 'add_cloth' and 'physics_add_cloth' by focusing on simulation rather than adding a modifier.

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 is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., cloth modifier already added) or scenarios where other tools would be more appropriate. Implies usage through examples but lacks explicit direction.

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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