blend-ai

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set_particle_rendering

Sets the rendering mode for an object's particle system, choosing whether particles render as paths, objects, collections, or not at all.

Instructions

Set rendering mode for an object's particle system.

Args: object_name: Name of the object with a particle system. render_type: Render type. One of: NONE, PATH, OBJECT, COLLECTION. instance_object: Object to instance (when render_type is OBJECT). instance_collection: Collection to instance (when render_type is COLLECTION).

Returns: Confirmation dict.

Input Schema

TableJSON Schema

Name	Required	Default
`object_name`	Yes
`render_type`	No	PATH
`instance_object`	No
`instance_collection`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv1.7.0Sep 28, 2026
- addedInput schema / additionalProperties
```
Added value: +false
```
- addedInput schema / properties / render_type / enum
```
Added value: +[
+  "COLLECTION",
+  "NONE",
+  "OBJECT",
+  "PATH"
+]
```
Addedv1.2.2May 3, 2026

TDQS

B3.1/5.0

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. It states a confirmation dict is returned, but discloses nothing about whether the change is reversible, what happens to existing render settings, whether it requires a specific mode or permissions, or failure behavior when no particle system 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?

Front-loaded one-line summary followed by a compact Args block and a one-line Returns note. Every line earns its place; only the Returns line is arguably redundant given the output schema.

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?

For a 4-param mutation tool with no annotations, the description covers parameters well and an output schema exists so return values need not be detailed. However, it omits default behavior, side effects, and error conditions, leaving a mutation's behavioral profile largely undisclosed.

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: all four parameters are documented, the render_type enum values are enumerated, and the conditions under which instance_object/instance_collection apply are spelled out. It falls short of noting the defaults (PATH, empty strings) that live only in the schema.

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 and resource: set the rendering mode for an object's particle system. That is clear enough for an agent to select it against most siblings, though it does not explicitly distinguish itself from nearby tools like set_particle_velocity or add_particle_system.

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 guidance on when to use this tool versus alternatives such as add_particle_system or set_particle_velocity, nor on prerequisites (e.g. that the object must already have a particle system). The conditional notes on instance_object/instance_collection are parameter semantics, not usage routing.

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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