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add_soft_body

Make a mesh object soft and wobbly by adding adjustable mass, stiffness, damping, and collision settings for jelly, cushions, or antennae.

Instructions

Make an object soft and wobbly: jelly, cushions, bellies, antennae.

Bake it with bake_physics. With goal on, vertices are pulled back to their shape (higher goal_strength is stiffer); with goal off the object sags and bounces freely, like a water balloon. Add collision to the floor.

Args: object_name: Mesh object. mass: Vertex mass, 0.001 to 50. goal: Pull vertices back toward the original shape. goal_strength: How strongly, 0.0 to 1.0. pull: Edge stiffness when stretched, 0.0 to 0.999. push: Edge stiffness when squashed, 0.0 to 0.999. bend: Resistance to bending, 0 to 10. damping: Edge spring damping, 0 to 50. friction: Air friction, 0 to 50. self_collision: Stop the body passing through itself (slower).

Returns: Dict with the soft body settings.

Input Schema

NameRequiredDescriptionDefault
bendNo
goalNo
massNo
pullNo
pushNo
dampingNo
frictionNo
object_nameYes
goal_strengthNo
self_collisionNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv3.0.0

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it explains the goal-on versus goal-off behavior, notes that self_collision is slower, and states the return type. It stops short of stating whether existing soft body settings are replaced and does not mention permissions or failure cases.

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 purpose and examples are front-loaded, then behavior, related tools, and a compact argument list follow. Given ten otherwise undocumented parameters, every sentence earns its place.

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

Completeness5/5

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

For a ten-parameter setup tool with no schema descriptions and no annotations, the description supplies the missing semantics, behavioral effects, and related-step guidance. The output schema exists, so brief return information is sufficient.

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

Parameters5/5

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: every one of the ten parameters is given a clear meaning and value range, including nuanced distinctions like pull versus push and goal versus goal_strength.

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 states a specific verb and effect: make an object soft and wobbly, with concrete examples (jelly, cushions, bellies, antennae). It also names the related bake_physics tool, so an agent can distinguish this setup step from the baking step.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives clear usage context: use bake_physics afterward, and add collision to the floor for interaction. It does not explicitly compare against siblings like add_cloth_sim or add_rigid_body, so the when-not guidance is implicit rather than complete.

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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